Building a credit card-first wedge into healthcare

Ness

ness

Many of us have made changes to data based on requirements that later evolve. By the time we realize it, it becomes impossible to roll back. Change isn't just a constant; it's an essential part of managing data that demands a sophisticated approach. Enter the Git-like functionality of Dremio's data catalog Nessie. Just as Git has become fundamental to software development, data engineers need similar tools to work in parallel, compare data versions, promote changes to production and roll back data when needed. Nessie provides data engineers with a Git-like version control system for managing data versions, branches, merges, and commits. This can be very helpful when multiple data engineers are working with and transforming data at the same time. Nessie allows each engineer to work in separate branches while maintaining a single source of truth in the form of the main branch. This functionality empowers data engineering teams to maintain data quality collaboratively in the face of unrelenting change. This article provides a step-by-step guide demonstrating how Nessie, Dremio and MinIO work together to enhance data quality and collaboration in your data engineering workflows. Whether you're a data engineer, ML engineer, or just a modern data lake enthusiast, this blog equips you with the knowledge and tools needed to effectively enhance your data versioning practices. Understanding the Basics: Nessie Workloads Nessie allows for Git-like workloads that let you test, develop and push to production. Let's break down some key concepts: Just like in Git, branches in Nessie allow you to work on different data engineering tasks concurrently. For example, you might have a branch for feature development, data cleaning and data transformation. Each branch can have its own set of data changes. Branches: In Nessie, a commit represents a snapshot of the data at a specific point in time. When you make changes to your data, you create a new commit, which records those changes. Commits are linked to a specific branch. When you need to revert your data to a stable or known-good state, Nessie makes it easy to select a specific commit and roll back to that data version. This ensures data quality and consistency. Commits: : Nessie allows you to merge the changes from one branch into another. This is similar to merging code changes in Git. When you merge a branch, the data changes made in that branch become part of the target branch. Merges The Components is a distributed analytics engine that operates as an open-source platform, offering an intuitive self-service interface for data exploration, transformation and collaborative work. Its design is grounded in a high-speed columnar memory format. Dremio Apache Arrow, We’ve already explored how to deploy Dremio with Kubernetes, and also how to . For additional information about Dremio, consult . query Iceberg tables on MinIO with Dremio Dremio Resources is high-performance object storage. Renowned for its exceptional and , MinIO serves as a pivotal component in building and maintaining modern data lake infrastructures. MinIO empowers architects to efficiently manage and store massive volumes of data on-prem, on bare metal, on the edge, or on any of the public clouds. MinIO speed scalability is an open table format suited for managing large volumes of data in data lakes. Unique features like time travel, dynamic schema evolution, and Partition Evolution make it a game-changer, allowing query engines to work concurrently on the same data safely and efficiently. See for more information about Iceberg features. Apache Iceberg MinIO The Definitive Guide to Lakehouse Architecture with Iceberg and Getting Started You’ll need the and for this tutorial. The easiest way to get both if you don’t already have them is to install Docker Desktop. Docker Engine Docker Compose This part of the tutorial is based on Dremio’s . You can get the repo for this project . blog post here To begin, open a terminal and navigate to the folder where you cloned/downloaded the repo, and run the command below to start up Dremio. docker-compose up dremio Wait a few moments and then navigate to to access Dremio. Update the requested fields and then click Next. http://localhost:9047 Next, run the following command to start MinIO. docker-compose up minio The final command below will start up Nessie. docker-compose up docker-compose up nessie Navigate to to log in to MinIO with the username and password of . You’ll be prompted to create a bucket. http://localhost:9001 minioadmin:minioadmin Make one named . iceberg-datalake Then head back over to Dremio at and click on Add Source and select Nessie. http://localhost:9047 Set the Name to nessie Set the endpoint URL to http://nessie:19120/api/v2 Set the authentication to none Don’t click Save yet. Instead, in the navigation panel on the left, click Storage. MinIO is S3-API compatible object storage and can use the same connection pathways as AWS S3. For your access key, set minioadmin For your secret key, set minioadmin Set root path to /iceberg-datalake Scroll down for the next set of instructions. Click on the button under to create and configure the following properties. Add Property Connection Properties to fs.s3a.path.style.access true to fs.s3a.endpoint minio:9000 to dremio.s3.compat true Uncheck Encrypt connection Then click Save. You should now see Nessie Catalogs in your data sources. Create a Data Source In Dremio navigate to SQL Runner on the left-hand side. Make sure that in the upper right area of the text editor is set to our Nessie source. Otherwise, you will have to reference the context like instead of just to run this query. Copy and paste the SQL below and run. Context nessie.SalesData SalesData CREATE TABLE SalesData (
    id INT,
    product_name VARCHAR,
    sales_amount DECIMAL,
    transaction_date DATE
) PARTITION BY (transaction_date); Run the query below to insert data into the table you just created. INSERT INTO SalesData (id, product_name, sales_amount, transaction_date)
VALUES
    (1, 'ProductA', 1500.00, '2023-10-15'),
    (2, 'ProductB', 2000.00, '2023-10-15'),
    (3, 'ProductA', 1200.00, '2023-10-16'),
    (4, 'ProductC', 1800.00, '2023-10-16'),
    (5, 'ProductB', 2200.00, '2023-10-17'); Navigate back to MinIO to see that your data lake has been populated with the Iceberg tables. Branching and Merging with Nessie Return to Dremio at . Begin by querying a table on the main branch using the syntax: http://localhost:9047 AT BRANCH SELECT * FROM  nessie.SalesData AT BRANCH main; Create an ETL (Extract Transform and Load) branch to allow you to play around with and transform data without impacting production. CREATE BRANCH etl_06092023 in nessie Within the ETL branch, insert new data into the table: USE BRANCH etl_06092023 in nessie;
INSERT INTO nessie.SalesData (id, product_name, sales_amount, transaction_date) VALUES
(6, 'ProductC', 1400.00, '2023-10-18'); Confirm the immediate availability of the new data within the ETL branch: SELECT * FROM nessie.SalesData AT BRANCH etl_06092023; Note the isolation of changes from users on the main branch: SELECT * FROM nessie.SalesData AT BRANCH main; Merge the changes from the ETL branch back into the main branch: MERGE BRANCH etl_06092023 INTO main in nessie; Select the main branch again to see that the changes have indeed been merged. SELECT * FROM nessie.SalesData AT BRANCH main This branching strategy enables data engineers to independently handle numerous transactions across multiple tables. When they are ready, data engineers can merge these transactions into a single, comprehensive multi-table transaction within the main branch. Conclusion This blog post delved into the power of Git-like version control in data engineering, emphasizing how seamlessly manages data versions, branches and merges. This step-by-step guide demonstrates how Nessie, in collaboration with Dremio and MinIO, as the object storage foundation, enhances data quality and collaboration in data engineering workflows. Nessie Let us know what your data lakehouse looks like at or on . hello@minio.io our Slack channel Also appears . here

Data Lake Mysteries Revealed: Nessie, Dremio, and MinIO Make Waves

ডেটা লেক রহস্য প্রকাশিত হয়েছে: নেসি, ড্রেমিও এবং মিনিও মেক ওয়েভস

Data-Lake-Rätsel aufgedeckt: Nessie, Dremio und MinIO sorgen für Aufsehen

Misterios del lago de datos revelados: Nessie, Dremio y MinIO hacen olas

Les mystères du Data Lake révélés : Nessie, Dremio et MinIO font des vagues

डेटा लेक रहस्य का खुलासा: नेस्सी, ड्रेमियो और मिनिओ मेक वेव्स

データレイクの謎が明らかに: Nessie、Dremio、MinIO が波紋を起こす

데이터 레이크의 미스터리 공개: Nessie, Dremio 및 MinIO가 물결을 일으키다

Mistérios do Data Lake revelados: Nessie, Dremio e MinIO fazem ondas

Тайны озера данных раскрыты: Несси, Дремио и MinIO вызывают фурор

Data Lake'in Gizemleri Ortaya Çıktı: Nessie, Dremio ve MinIO Dalga Yaratıyor

Những bí ẩn về hồ dữ liệu được tiết lộ: Nessie, Dremio và MinIO tạo nên làn sóng

数据湖谜团揭开：Nessie、Dremio 和 MinIO 掀起波澜

FTC v. Amazon Court Filing, retrieved on Sep 26, 2023, is part of . You can jump to any part in this filing . This is part 60 of 80. HackerNoon’s Legal PDF Series here COUNT IV: UNFAIR METHOD OF COMPETITION (15 U.S.C. § 45(a)) 457. Plaintiff FTC re-alleges and incorporates by reference the allegations in paragraphs 1-456 above. 458. Amazon has engaged in an unfair method of competition, called Project Nessie, that (redacted) 459. Amazon designed and used its Project Nessie pricing system (redacted) 460. Amazon’s Project Nessie pricing system (redacted) 461 (Redacted) 462. Amazon’s use of its Project Nessie pricing system is an unfair method of competition in violation of Section 5(a) of the FTC Act, 15 U.S.C. § 45(a). 463. There is no valid and cognizable justification for Amazon’s use of Project Nessie. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 2:23-cv-01495 retrieved on October 2, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. ftc.gov

How Amazon's Project Nessie Supports Its Anti-Competitive Tactics

For Entrepreneurs, Endurance is more Important than Intellect 

Getting Started With Apache Iceberg and Resources if You Would Like To Go Further

Apache Iceberg is an innovative data lakehouse table format designed to revolutionize how you manage large-scale data across various storage layers, such as Hadoop and AWS S3. By treating these diverse storage solutions as a cohesive, universal database, Apache Iceberg facilitates seamless integration with numerous tools, platforms, and interfaces, enhancing both flexibility and accessibility. One of the standout features of Apache Iceberg is its support for ACID transactions, which ensures data integrity by enabling atomicity, consistency, isolation, and durability in data processing operations. Additionally, Apache Iceberg's Time Travel capability allows users to query historical versions of data, providing valuable insights into data changes over time. The format also supports dynamic schema evolution and partitioning adjustments without downtime, which simplifies the management of data as it grows and changes. Apache Iceberg also includes a host of other advanced features that enhance data usability and management. These include snapshot isolation for concurrent data access, upserts and deletes within tables, and handling large-scale metadata efficiently. To help you harness the full potential of Apache Iceberg, our latest blog series gathers a collection of straightforward, hands-on tutorials. These guides are designed to provide you with practical experience in working with Apache Iceberg, from setting up your first table to executing complex data operations. Whether you're a data scientist, engineer, or analyst, these tutorials offer a valuable opportunity to enhance your data handling skills and leverage Apache Iceberg’s powerful features in your projects. Self-Contained Exercises These are completely self-contained and can be done from your laptop; all infrastructure is spun up as Docker containers. End-to-End Basic Data Engineering Tutorial (Spark, Dremio, Superset)
From Postgres to Dashboards with Dremio and Apache Iceberg
From SQLServer to Dashboards with Dremio and Apache Iceberg
From MongoDB to Dashboards with Dremio and Apache Iceberg
Intro to Dremio, Nessie, and Apache Iceberg on Your Laptop
Using Flink with Apache Iceberg and Nessie
Getting Started with Project Nessie, Apache Iceberg, and Apache Spark Using Docker Require Online Services These are tutorials that will require signing up for services like Upsolver, Dremio, AWS, and others to complete. How to Convert JSON Files Into an Apache Iceberg Table with Dremio
How to Convert CSV Files into an Apache Iceberg table with Dremio
Run Graph Queries on Apache Iceberg Tables with Dremio & Puppygraph
BI Dashboards with Apache Iceberg Using AWS Glue and Apache Superset
Streaming and Batch Data Lakehouses with Apache Iceberg, Dremio and Upsolver
Git for Data with Dremio’s Lakehouse Catalog: Easily Ensure Data Quality in Your Data Lakehouse
How to Create a Lakehouse with Airbyte, S3, Apache Iceberg, and Dremio Video Playlists: Hands-On With Apache Iceberg


Apache Iceberg Lakehouse Engineering 101
In summary, Apache Iceberg is more than just a data storage format; it is a comprehensive solution that adapts to the complexities of modern data environments, ensuring robust data integrity, flexibility, and scalability. Apache Iceberg is an innovative data lakehouse table format designed to revolutionize how you manage large-scale data across various storage layers, such as Hadoop and AWS S3. By treating these diverse storage solutions as a cohesive, universal database, Apache Iceberg facilitates seamless integration with numerous tools, platforms, and interfaces, enhancing both flexibility and accessibility. One of the standout features of Apache Iceberg is its support for ACID transactions, which ensures data integrity by enabling atomicity, consistency, isolation, and durability in data processing operations. Additionally, Apache Iceberg's Time Travel capability allows users to query historical versions of data, providing valuable insights into data changes over time. The format also supports dynamic schema evolution and partitioning adjustments without downtime, which simplifies the management of data as it grows and changes. Apache Iceberg also includes a host of other advanced features that enhance data usability and management. These include snapshot isolation for concurrent data access, upserts and deletes within tables, and handling large-scale metadata efficiently. To help you harness the full potential of Apache Iceberg, our latest blog series gathers a collection of straightforward, hands-on tutorials. These guides are designed to provide you with practical experience in working with Apache Iceberg, from setting up your first table to executing complex data operations. Whether you're a data scientist, engineer, or analyst, these tutorials offer a valuable opportunity to enhance your data handling skills and leverage Apache Iceberg’s powerful features in your projects. Self-Contained Exercises These are completely self-contained and can be done from your laptop; all infrastructure is spun up as Docker containers. End-to-End Basic Data Engineering Tutorial (Spark, Dremio, Superset) From Postgres to Dashboards with Dremio and Apache Iceberg From SQLServer to Dashboards with Dremio and Apache Iceberg From MongoDB to Dashboards with Dremio and Apache Iceberg Intro to Dremio, Nessie, and Apache Iceberg on Your Laptop Using Flink with Apache Iceberg and Nessie Getting Started with Project Nessie, Apache Iceberg, and Apache Spark Using Docker End-to-End Basic Data Engineering Tutorial (Spark, Dremio, Superset) End-to-End Basic Data Engineering Tutorial (Spark, Dremio, Superset) End-to-End Basic Data Engineering Tutorial (Spark, Dremio, Superset) From Postgres to Dashboards with Dremio and Apache Iceberg From Postgres to Dashboards with Dremio and Apache Iceberg From Postgres to Dashboards with Dremio and Apache Iceberg From SQLServer to Dashboards with Dremio and Apache Iceberg From SQLServer to Dashboards with Dremio and Apache Iceberg From SQLServer to Dashboards with Dremio and Apache Iceberg From MongoDB to Dashboards with Dremio and Apache Iceberg From MongoDB to Dashboards with Dremio and Apache Iceberg From MongoDB to Dashboards with Dremio and Apache Iceberg Intro to Dremio, Nessie, and Apache Iceberg on Your Laptop Intro to Dremio, Nessie, and Apache Iceberg on Your Laptop Intro to Dremio, Nessie, and Apache Iceberg on Your Laptop Using Flink with Apache Iceberg and Nessie Using Flink with Apache Iceberg and Nessie Using Flink with Apache Iceberg and Nessie Getting Started with Project Nessie, Apache Iceberg, and Apache Spark Using Docker Getting Started with Project Nessie, Apache Iceberg, and Apache Spark Using Docker Getting Started with Project Nessie, Apache Iceberg, and Apache Spark Using Docker Require Online Services These are tutorials that will require signing up for services like Upsolver, Dremio, AWS, and others to complete. How to Convert JSON Files Into an Apache Iceberg Table with Dremio How to Convert CSV Files into an Apache Iceberg table with Dremio Run Graph Queries on Apache Iceberg Tables with Dremio & Puppygraph BI Dashboards with Apache Iceberg Using AWS Glue and Apache Superset Streaming and Batch Data Lakehouses with Apache Iceberg, Dremio and Upsolver Git for Data with Dremio’s Lakehouse Catalog: Easily Ensure Data Quality in Your Data Lakehouse How to Create a Lakehouse with Airbyte, S3, Apache Iceberg, and Dremio How to Convert JSON Files Into an Apache Iceberg Table with Dremio How to Convert JSON Files Into an Apache Iceberg Table with Dremio How to Convert JSON Files Into an Apache Iceberg Table with Dremio How to Convert CSV Files into an Apache Iceberg table with Dremio How to Convert CSV Files into an Apache Iceberg table with Dremio How to Convert CSV Files into an Apache Iceberg table with Dremio Run Graph Queries on Apache Iceberg Tables with Dremio & Puppygraph Run Graph Queries on Apache Iceberg Tables with Dremio & Puppygraph Run Graph Queries on Apache Iceberg Tables with Dremio & Puppygraph BI Dashboards with Apache Iceberg Using AWS Glue and Apache Superset BI Dashboards with Apache Iceberg Using AWS Glue and Apache Superset BI Dashboards with Apache Iceberg Using AWS Glue and Apache Superset Streaming and Batch Data Lakehouses with Apache Iceberg, Dremio and Upsolver Streaming and Batch Data Lakehouses with Apache Iceberg, Dremio and Upsolver Streaming and Batch Data Lakehouses with Apache Iceberg, Dremio and Upsolver Git for Data with Dremio’s Lakehouse Catalog: Easily Ensure Data Quality in Your Data Lakehouse Git for Data with Dremio’s Lakehouse Catalog: Easily Ensure Data Quality in Your Data Lakehouse Git for Data with Dremio’s Lakehouse Catalog: Easily Ensure Data Quality in Your Data Lakehouse How to Create a Lakehouse with Airbyte, S3, Apache Iceberg, and Dremio How to Create a Lakehouse with Airbyte, S3, Apache Iceberg, and Dremio How to Create a Lakehouse with Airbyte, S3, Apache Iceberg, and Dremio Video Playlists: Hands-On With Apache Iceberg Apache Iceberg Lakehouse Engineering 101
In summary, Apache Iceberg is more than just a data storage format; it is a comprehensive solution that adapts to the complexities of modern data environments, ensuring robust data integrity, flexibility, and scalability. Hands-On With Apache Iceberg Hands-On With Apache Iceberg Hands-On With Apache Iceberg Hands-On With Apache Iceberg Apache Iceberg Lakehouse Engineering 101 In summary, Apache Iceberg is more than just a data storage format; it is a comprehensive solution that adapts to the complexities of modern data environments, ensuring robust data integrity, flexibility, and scalability. Apache Iceberg Lakehouse Engineering 101 Apache Iceberg Lakehouse Engineering 101 Apache Iceberg Lakehouse Engineering 101 In summary, Apache Iceberg is more than just a data storage format; it is a comprehensive solution that adapts to the complexities of modern data environments, ensuring robust data integrity, flexibility, and scalability.

16 Guides to Get You Started with Apache Iceberg

Metaphysics and Mathematics 2: The Complex Space of Prime Numbers

The Multitudes Within "Be yourself." The well-meaning advice plastered on motivational posters and whispered by concerned aunts the world over. Sounds nice in theory, right? A comforting idea for those moments when we feel like imposters, fumbling awkwardly through new job interviews or high-stakes presentations. But here's the thing…it's pretty terrible, lazy advice. Why? Because it's woefully incomplete and often downright lazy. Let me paint you a picture. Imagine gearing up for an important meeting. You've spent days carefully crafting your pitch, meticulously researching every nuanced detail. You step into that room, ready to crush it…and the first thing someone tells you is, "Just be yourself." …Helpful. Thanks a bunch. See, the trouble is are not a monolith. We all contain a complex cocktail of personalities, strengths, and quirks. Which version of yourself should you "be"? The goofy, pun-loving friend from brunch? The ultra-competitive version you channel on the basketball court? The quiet, introspective poet who emerges in solitude? you The Multitudes Within The truth is, there's no single "you" to whip out for every situation life tosses your way. "Being yourself" implies a static, unchanging identity, and that, my friends, is a myth. We grow, we evolve, we . adapt Imagine yourself as an RPG character (remember those?). You have different skill sets – charisma, intellect, focus, whatever your build focuses on. Now, when facing different challenges, you wisely choose which of those skills to bring to the forefront. That's not being fake, that's being strategic. So, instead of "be yourself," I propose an upgrade: "You have multitudes. Which version of yourself is suited to the task? The negotiator, the visionary, the empathetic listener… deploy strategically." The School of Applied Self-ness Let's break this down into a few actionable steps: It's time to Marie Kondo your personality. Not everything sparks joy, but it's all useful data. Start by listing your strengths, weaknesses, and the different "roles" you play in life. Brutal honesty is your friend here. The Inventory: Just like a good spy scopes out the scene before a mission, analyze the situation you're about to enter. What's the goal? Who's the audience? What outcome do you want? Situational Awareness: Time to play to your strengths. If a negotiation calls for cool-headed logic, maybe downplay the emotional side and channel your inner data analyst. Need to inspire a team? Time for the charismatic hype-machine to take the stage. Skill Match: Here’s some real-world scenarios where this approach pays off: Scenario 1: The Difficult Conversation Nobody likes confrontation, but sometimes you need to address a tough issue. Maybe it's a conflict with a coworker, a delicate piece of feedback, or a heart-to-heart with a loved one. In these situations, the "blunt and brutally honest" version of you might not be the best ambassador. Focus on understanding the other person's perspective. Let your genuine compassion lead as you carefully build a bridge to connect perspectives. Think of yourself as a skilled diplomat, negotiating a peaceful resolution for all parties involved. Deploy the Empath: Scenario 2: The Big Presentation You're up on stage, about to deliver the pitch of a lifetime. This isn't the time for your shy, self-deprecating side. Time to bring the thunder. Channel boundless enthusiasm and infectious energy. Paint a vivid picture of the future, the possibilities, the sheer awesomeness of the idea you're presenting. Let your passion carry the day, sweeping the audience along with you. Deploy the Visionary: Scenario 3: The Job Interview First impressions matter. You need to exude competence and confidence, but also build a genuine connection. Where's the sweet spot? Balance warmth with professionalism. Showcase your research on the role and company, weaving in how your particular skills and experiences make you the perfect fit. Think of yourself as a puzzle piece, demonstrating exactly how you'll slot into their larger picture. Deploy the Strategist: The Art of the Shift Now, does this mean you're "faking it"? No. You're not suddenly a different person, just emphasizing certain traits over others. The key is to understand your own defaults. If you're naturally analytical, you might need to work on amplifying your charisma. If you're a people-pleaser, it'll be valuable to practice assertive communication. This isn't about losing yourself; it's about gaining self-awareness. The more you understand your strengths and weaknesses, the more you can consciously play to the situation at hand. A Word on Personal Growth This approach naturally ties into your personal development journey. As you learn more, gain experience, and challenge yourself, the pool of "personas" you can tap into expands. What might feel forced now can become second nature with practice. A Caveat Does this mean you need to be ruthlessly calculated with every interaction? Absolutely not. Authenticity is still key, but let's think of it as authenticity. It's about showcasing the "you" that's best equipped to get the job done. calibrated And the elephant in the room. What about truly close relationships? Should you also be constantly strategizing with your friends, partners, or family? Here's where a balanced approach is crucial. While a degree of adaptability is always useful, your closest circle deserves a healthy dose of the unfiltered, messy, REAL you. Those are the people who earn the right to see everything, even the not-so-shiny parts. Until then, remember – you're not just one thing. You're a dynamic, adaptable force. Unleash the right part of yourself at the right time, and the world won't know what hit it. Have a great weekend! Scott Also appears . here

It's Time to Ditch "Be Yourself"

এটি "নিজেকে হও" ত্যাগ করার সময়

Es ist Zeit, „Sei du selbst“ aufzugeben

Es hora de deshacerse del "sé tú mismo"

Il est temps d’abandonner « Soyez vous-même »

अब "खुद बनो" को छोड़ने का समय आ गया है

「自分らしくあること」を捨てる時が来た

이제 "Be Yourself"를 버릴 시간입니다

É hora de abandonar o "seja você mesmo"

Пришло время отказаться от «будь собой»

"Kendin Ol"u Bırakmanın Zamanı Geldi

Đã đến lúc từ bỏ "Hãy là chính mình"

是时候放弃“做你自己”了

How are you, hacker?
🪐 has got you covered with fresh content from our trending stories of the day! Set email preference . Want to know what's trending right now?: The Techbeat by HackerNoon here To Focus or Not Focus: How to Find the Right Product-Market Fit By [ 3 Min read ]
To all the product managers out there searching for that elusive product-market fit, remember to keep your eyes on the prize and focus on what matters most! @densmr Read More. Elevating Product Management with Marketing Insights By [ 9 Min read ]
Learn how to having marketing skills makes you a better product manager and how they help build great products. @dashadobrego Read More. Breaking the CPO Bubble: My Strategy for Staying Close to Our Products By [ 3 Min read ]
Explore a CPO's journey in "Breaking the CPO Bubble," detailing strategies for connecting with products and teams and enhancing customer alignment. @densmr Read More. How to Manage a Product Backlog in a Fast-Growing B2B Startup By [ 7 Min read ]
In this article, I’d like to share my tips for working as a product manager in fast-growing startups. I’ll also explain how these tips could be used in B2B prod @dashadobrego Read More. Everything You Need to Know to Implement Generative AI for Your Enterprise By [ 8 Min read ]
The easiest way to conceptualize what is possible with Generative AI is to imagine a customized Large Language Model running inside your firewall. @minio Read More. How to Teach People to Make the Right Decisions and Delegate Important Business Tasks With no Stress By [ 6 Min read ]
Discover effective strategies for decision-making and delegation in business, fostering a culture of responsibility and continuous improvement. @densmr Read More. Is AGI Getting Closer? Anthropic's Claude 3 Opus Model Shows Glimmers of Metacognitive Reasoning By [ 5 Min read ]
Anthropic's new LLM told prompters it knew they were testing it @mikeyoung44 Read More. Nintendo Breaks Its Silence On Palworld By [ 4 Min read ]
Nintendo finally broke its silence after Palworld’s launch raised controversy among the Pokemon community. @playerauctions Read More. Sam Mangel to Sam Bankman-Fried: Acceptance is the Path Forward By [ 4 Min read ]
The approach SBF’s legal team are taking toward sentence mitigation makes one thing clear: the former FTX CEO has not yet accepted what he did was wrong. @drewchapin Read More. Data Lake Mysteries Revealed: Nessie, Dremio, and MinIO Make Waves By [ 6 Min read ]
Let's see how Nessie, Dremio and MinIO work together to enhance data quality and collaboration in your data engineering workflows. @minio Read More. 7 Monetization Options to Consider for Your Blog By [ 5 Min read ]
Looking for ways to generate stable revenue through your blog? The article showcases a few noteworthy options for you to consider. @griffinjt Read More. 5 Low-Cost Cybersecurity Measures SMBs Can’t Afford to Not Implement By [ 4 Min read ]
A successful cyber attack can be devastating; many cybersecurity measures that can help SMBs can be implemented at surprisingly little cost. @jonstojanmedia Read More. GitHub Copilot Review: Does it Really Give a 55% Speed Boost to Development? By [ 7 Min read ]
This article presents a GitHub Copilot review and assesses its impact on enhancing development speed in real-life scenarios. @elekssoftware Read More. After 6 Months of Working on a CodeGen Dev Tool (GPT Pilot), This Is What I Learned By [ 13 Min read ]
What I learned in 6 months of working on the most powerful CodeGen dev tool GPT Pilot @zvone187 Read More. What is the Language Processing Unit (LPU)? Is It GPU's Rival? By [ 7 Min read ]
So: What is LPU, how does it work, and where is Groq (such an unfortunate name, given Musk’s Grok is all over the media) coming from? @kseniase Read More. How to Analyze Anything - Master Data Analysis With ChatGPT (Beginner's Tutorial) By [ 3 Min read ]
Today, we’re diving into an exciting feature within ChatGPT that has the potential to enhance your productivity by 10, 20, 30, or even 40%. @proflead Read More. Chrome Password Manager Betrayed My Trust 13 Years Ago. I Never Forgot By [ 10 Min read ]
Chrome's broken trust led to Neulock: a password manager built on user control, not encryption & blind faith. Learn the 3 security principles behind it. @lucasneves Read More. Mixing the Cross-Chain magic with Tokenized Real Worlds Assets By [ 4 Min read ]
The future of finance is with tokenized RWAs and cross-chain DeFi; dig into real world assets on Avalanche and ICON. @helloicon Read More. Tokenizing Real-World Assets (RWA) Part 1: A Deep Dive into ERC-3643 By [ 6 Min read ]
Discover the concept of  Real-World Assets (RWA) tokenization and its benefits, along with an examination of the ERC-3643 standard tailored for this purpose. @leonidcryptonstudio Read More. Bitcoin's Surge Past $60,000: Rally or Short-Lived Surge? By [ 4 Min read ]
Bitcoin has crossed the $60,000 mark, and it looks like this is not the limit yet. How sustainable is this growth and what to expect further? 🧑‍💻 What happened in your world this week? It's been said that , , . Feeling stuck? We got you covered ⬇️⬇️⬇️ We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.
See you on Planet Internet! With love,
The HackerNoon Team ✌️ @dshishov Read More. writing can help consolidate technical knowledge establish credibility and contribute to emerging community standards ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME

The TechBeat: To Focus or Not Focus: How to Find the Right Product-Market Fit (3/8/2024)

This paper is available on arxiv under CC 4.0 license. Authors: (1) Thomas Pethick, EPFL (LIONS) thomas.pethick@epfl.ch; (2) Wanyun Xie, EPFL (LIONS) wanyun.xie@epfl.ch; (3) Volkan Cevher, EPFL (LIONS) volkan.cevher@epfl.ch. Table of Links Abstract & Introduction Related work Setup Inexact Krasnosel’ski˘ı-Mann iterations Approximating the resolvent Last iterate under cohypomonotonicity Analysis of Lookahea Experiments Conclusion & limitations Acknowledgements & References 10 Acknowledgements This work was supported by Google. This work was supported by Hasler Foundation Program: Hasler Responsible AI (project number 21043). This work was supported by the Swiss National Science Foundation (SNSF) under grant number 200021_205011. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement n° 725594 - time-data). References Banach, S. Sur les opérations dans les ensembles abstraits et leur application aux équations intégrales. Fund. math, 3(1):133–181, 1922. Bauschke, H. H. and Combettes, P. L. Convex analysis and monotone operator theory in Hilbert spaces. CMS Books in Mathematics. Springer, 2017. ISBN 978-3-319-48310-8. Bauschke, H. H., Moursi, W. M., and Wang, X. Generalized monotone operators and their averaged resolvents. Mathematical Programming, 189(1):55–74, 2021. Bertsekas, D. P. Incremental proximal methods for large scale convex optimization. Mathematical programming, 129(2):163–195, 2011. Bianchi, P. On the convergence of a stochastic proximal point algorithm. In CAMSAP, 2015. Bravo, M. and Cominetti, R. Stochastic fixed-point iterations for nonexpansive maps: Convergence and error bounds. arXiv preprint arXiv:2208.04193, 2022. Brézis, H. and Lions, P. L. Produits infinis de résolvantes. Israel Journal of Mathematics, 29(4): 329–345, 1978. Cevher, V., Piliouras, G., Sim, R., and Skoulakis, S. Min-max optimization made simple: Approximating the proximal point method via contraction maps, 2023. URL https://arxiv.org/abs/ 2301.03931. Chavdarova, T., Pagliardini, M., Stich, S. U., Fleuret, F., and Jaggi, M. Taming GANs with Lookahead-Minmax. arXiv preprint arXiv:2006.14567, 2020. Combettes, P. L. Quasi-Fejérian analysis of some optimization algorithms. In Studies in Computational Mathematics, volume 8, pp. 115–152. Elsevier, 2001. Combettes, P. L. and Pennanen, T. Proximal methods for cohypomonotone operators. SIAM journal on control and optimization, 43(2):731–742, 2004. Diakonikolas, J., Daskalakis, C., and Jordan, M. I. Efficient methods for structured nonconvexnonconcave min-max optimization. In International Conference on Artificial Intelligence and Statistics, pp. 2746–2754. PMLR, 2021. Eckstein, J. and Bertsekas, D. P. On the Douglas—Rachford splitting method and the proximal point algorithm for maximal monotone operators. Mathematical Programming, 55(1):293–318, 1992. Gidel, G., Berard, H., Vignoud, G., Vincent, P., and Lacoste-Julien, S. A variational inequality perspective on generative adversarial networks. arXiv preprint arXiv:1802.10551, 2018. Gorbunov, E., Loizou, N., and Gidel, G. Extragradient method: O (1/k) last-iterate convergence for monotone variational inequalities and connections with cocoercivity. In International Conference on Artificial Intelligence and Statistics, pp. 366–402. PMLR, 2022a. Gorbunov, E., Taylor, A., Horváth, S., and Gidel, G. Convergence of proximal point and extragradientbased methods beyond monotonicity: the case of negative comonotonicity. arXiv preprint arXiv:2210.13831, 2022b. Grimmer, B., Lu, H., Worah, P., and Mirrokni, V. The landscape of the proximal point method for nonconvex–nonconcave minimax optimization. Mathematical Programming, pp. 1–35, 2022. Ha, J. and Kim, G. On convergence of Lookahead in smooth games. In International Conference on Artificial Intelligence and Statistics, pp. 4659–4684. PMLR, 2022. Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S. GANs trained by a two time-scale update rule converge to a local Nash equilibrium. Advances in neural information processing systems, 30, 2017. Hsieh, Y.-P., Mertikopoulos, P., and Cevher, V. The limits of min-max optimization algorithms: Convergence to spurious non-critical sets. In International Conference on Machine Learning, pp. 4337–4348. PMLR, 2021. Iusem, A. N., Pennanen, T., and Svaiter, B. F. Inexact variants of the proximal point algorithm without monotonicity. SIAM Journal on Optimization, 13(4):1080–1097, 2003. Korpelevich, G. Extragradient method for finding saddle points and other problems. Matekon, 13(4): 35–49, 1977. Krizhevsky, A., Hinton, G., et al. Learning multiple layers of features from tiny images. 2009. Lee, S. and Kim, D. Fast extra gradient methods for smooth structured nonconvex-nonconcave minimax problems. Advances in Neural Information Processing Systems, 34:22588–22600, 2021. Luo, Y. and Tran-Dinh, Q. Extragradient-type methods for co-monotone root-finding problems. McMahan, B., Moore, E., Ramage, D., Hampson, S., and y Arcas, B. A. Communication-efficient learning of deep networks from decentralized data. In Artificial intelligence and statistics, pp. 1273–1282. PMLR, 2017. Miyato, T., Kataoka, T., Koyama, M., and Yoshida, Y. Spectral normalization for generative adversarial networks. arXiv preprint arXiv:1802.05957, 2018. Nemirovski, A. Prox-method with rate of convergence o (1/t) for variational inequalities with Lipschitz continuous monotone operators and smooth convex-concave saddle point problems. SIAM Journal on Optimization, 15(1):229–251, 2004. Nichol, A., Achiam, J., and Schulman, J. On first-order meta-learning algorithms. arXiv preprint arXiv:1803.02999, 2018. Obukhov, A., Seitzer, M., Wu, P.-W., Zhydenko, S., Kyl, J., and Lin, E. Y.-J. High-fidelity performance metrics for generative models in PyTorch, 2020. URL https://github.com/toshas/ torch-fidelity. Version: 0.3.0, DOI: 10.5281/zenodo.4957738. Opial, Z. Weak convergence of the sequence of successive approximations for nonexpansive mappings. Bulletin of the American Mathematical Society, 73(4):591–597, 1967. Patrascu, A. and Irofti, P. Stochastic proximal splitting algorithm for composite minimization. Optimization Letters, 15(6):2255–2273, 2021. Patrascu, A. and Necoara, I. Nonasymptotic convergence of stochastic proximal point methods for constrained convex optimization. The Journal of Machine Learning Research, 18(1):7204–7245, 2017. Pethick, T., Latafat, P., Patrinos, P., Fercoq, O., and Cevher, V. Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems. In International Conference on Learning Representations, 2022. Pethick, T., Fercoq, O., Latafat, P., Patrinos, P., and Cevher, V. Solving stochastic weak Minty variational inequalities without increasing batch size. In The Eleventh International Conference on Learning Representations, 2023. Pushkin, D. and Barba, L. Multilayer Lookahead: a nested version of Lookahead. arXiv preprint arXiv:2110.14254, 2021. Rockafellar, R. T. Monotone operators and the proximal point algorithm. SIAM journal on control and optimization, 14(5):877–898, 1976.

Stable Nonconvex-Nonconcave Training via Linear Interpolation: Acknowledgements & References

Alex Merced is a developer advocate for Dremio and co-Author of O’Reilly’s “Apache Iceberg: The Definitive Guide” Apache Iceberg is disrupting the data landscape, offering a new paradigm where data is not confined to the storage system of a chosen data warehouse vendor. Instead, it resides in your own storage, accessible by multiple tools. A built on your data lake as the storage layer, offers limitless configuration possibilities. Among the various options for constructing an Apache Iceberg lakehouse, the Dremio Data Lakehouse Platform stands out as one of the most straightforward, rapid, and cost-effective choices. This platform has gained popularity for on-premises migrations, implementing data mesh strategies, enhancing BI dashboards, and more. data lakehouse, which is essentially a modular data warehouse In this article, we will explore ten reasons why the combination of Apache Iceberg and the Dremio platform is exceptionally powerful. We will delve into five reasons to choose Apache Iceberg over other table formats and five reasons to opt for the Dremio platform when considering Semantic Layers, Query Engines, and Lakehouse Management. 5 Reasons to Choose Apache Iceberg Over Other Table Formats Apache Iceberg is not the only table format available; . All three formats provide a core set of features, enabling database-like tables on your data lake with capabilities such as ACID transactions, time travel, and schema evolution. However, there are several unique aspects that make Apache Iceberg a noteworthy option to consider. Delta Lake and Apache Hudi are also key players in this domain 1. Partition Evolution Apache Iceberg distinguishes itself with a feature known as partition evolution, which allows users to modify their partitioning scheme at any time without the need to rewrite the entire table. This capability is unique to Iceberg and carries significant implications, particularly for tables at the petabyte scale, where altering partitioning can be a complex and costly process. Partition evolution facilitates the optimization of data management, as it enables users to easily revert any changes to the partitioning scheme by simply rolling back to a previous snapshot of the table. This flexibility is a considerable advantage in managing large-scale data efficiently. 2. Hidden Partitioning Apache Iceberg introduces a unique feature called hidden partitioning, which significantly simplifies the workflows for both data engineers and data analysts. In traditional partitioning approaches, data engineers often need to create additional partitioning columns derived from existing ones, which not only increases storage requirements but also complicates the data ingestion process. Additionally, data analysts must be cognizant of these extra columns; failing to filter by the partition column could lead to a full table scan, undermining efficiency. However, with Apache Iceberg's hidden partitioning, the system can partition tables based on the transformed value of a column, with this transformation tracked in the metadata, eliminating the need for physical partitioning columns in the data files. This means that analysts can apply filters directly on the original columns and still benefit from the optimized performance of partitioning. This feature streamlines operations for both data engineers and analysts, making the process more efficient and less prone to error. 3. Versioning Versioning is an invaluable feature that facilitates isolating changes, executing rollbacks, simultaneously publishing numerous changes across different objects, and creating zero-copy environments for experimentation and development. While each table format records a single chain of changes, allowing for rollbacks, Apache Iceberg uniquely incorporates branching, tagging, and merging as integral aspects of its core table format. Furthermore, Apache Iceberg stands out as the sole format presently compatible with Nessie, an open-source project that extends versioning capabilities to include commits, branches, tags, and merges at the multi-table catalog , thereby unlocking a plethora of new possibilities. level These advanced versioning features in Apache Iceberg are accessible through ergonomic SQL interfaces, making them user-friendly and easily integrated into data workflows. In contrast, other formats typically rely on file-level versioning, which necessitates the use of command-line interfaces (CLIs) and imperative programming for management, making them less approachable and more cumbersome to use. This distinction underscores Apache Iceberg's advanced capabilities and its potential to significantly enhance data management practices. 4. Lakehouse Management Apache Iceberg is attracting a growing roster of vendors eager to assist in managing tables, offering services such as compaction, sorting, snapshot cleanup, and more. This support makes using Iceberg tables as straightforward as utilizing tables in a traditional database or data warehouse. In contrast, other table formats typically rely on a single tool or vendor for data management, which can lead to vendor lock-in. With Iceberg, however, there is a diverse array of vendors, including Dremio, Tabular, Upsolver, AWS, and Snowflake, each providing varying levels of table management features. This variety gives users the flexibility to choose a vendor that best fits their needs, enhancing Iceberg's appeal as a versatile and user-friendly data management solution. 5. Open Culture One of the most persuasive arguments for adopting Apache Iceberg is its dynamic open-source culture, which permeates its development and ecosystem. Development discussions take place on publicly accessible mailing lists and emails, enabling anyone to participate in and influence the format's evolution. The ecosystem is expanding daily, with an increasing number of tools offering both read and write support, reflecting the growing enthusiasm among vendors. This open environment provides vendors with the confidence to invest their resources in supporting Iceberg, knowing they are not at the mercy of a single vendor who could unpredictably alter or restrict access to the format. This level of transparency and inclusivity not only fosters innovation and collaboration but also ensures a level of stability and predictability that is highly valued in the tech industry. Dremio Dremio is a comprehensive data lakehouse platform that consolidates numerous functionalities, typically offered by different vendors, into a single solution. It unifies data analytics through data virtualization and a semantic layer, streamlining the integration and interpretation of data from diverse sources. Dremio's robust SQL query engine is capable of federating queries across various data sources, offering transparent acceleration to enhance performance. Additionally, Dremio's suite of lakehouse management features includes a Nessie-powered data catalog, which ensures data is versioned and easily transportable, alongside automated table maintenance capabilities. This integration of multiple key features into one platform simplifies the data management process, making Dremio a powerful and efficient tool for organizations looking to harness the full potential of their data lakehouse. 5. Apache Arrow One of the key reasons Dremio's SQL query engine outperforms other distributed query engines and data warehouses is its core reliance on . Apache Arrow facilitates the swift and efficient loading of data from various sources into a unified format optimized for speedy processing. Moreover, it introduces a transport protocol known as Apache Arrow Flight, which significantly reduces serialization/deserialization bottlenecks often encountered when transferring data over the network within a distributed system or between different systems. This integration of Apache Arrow at the heart of Dremio's architecture enhances its query performance, making it a powerful tool for data analytics. Apache Arrow, an in-memory data format increasingly recognized as the de facto standard for analytical processing 4. Columnar Cloud Cache One common bottleneck in querying a data lake based on object storage is the latency experienced when retrieving a large number of objects from storage. Additionally, each individual request can incur a cost, contributing to the overall storage access expenses. Dremio addresses these challenges with its C3 (Columnar Cloud Cache) feature, which caches frequently accessed data on the NVMe memory of nodes within the Dremio cluster. This caching mechanism enables rapid access to data during subsequent query executions that require the same information. As a result, the more queries that are run, the more efficient Dremio becomes. This not only enhances query performance over time but also reduces costs, making Dremio an increasingly cost-effective and faster solution as usage grows. This anti-fragile nature of Dremio, where it strengthens and improves with stress or demand, is a significant advantage for organizations looking to optimize their data querying capabilities. 3. Reflections Other engines often rely on materialized views, and BI extracts to accelerate queries, which can require significant manual effort to maintain. This process creates a broader array of objects that data analysts must track and understand when to use. Moreover, many platforms cannot offer this acceleration across all their compatible data sources. In contrast, Dremio introduces a unique feature called Reflections, which simplifies query acceleration without adding to the management workload of engineers or expanding the number of namespaces analysts need to be aware of. Reflections can be applied to any table or view within Dremio, allowing for the materialization of rows or the aggregation of calculations on the dataset. For data engineers, Dremio automates the management of these materializations, treating them as Iceberg tables that can be intelligently substituted when a query that would benefit from them is detected. Data analysts, on the other hand, continue to query tables and build dashboards as usual without needing to navigate additional namespaces. They will, however, experience noticeable performance improvements immediately without any extra effort. This streamlined approach not only enhances efficiency but also significantly reduces the complexity typically associated with optimizing query performance. 2. Semantic Layer Many query engines and data warehouses lack the capability to offer an organized, user-friendly interface for end users, a feature known as a semantic layer. This layer is crucial for providing logical, intuitive views for understanding and discovering data. Without this feature, organizations often find themselves needing to integrate services from additional vendors, which can introduce a complex web of dependencies and potential conflicts to manage. Dremio stands out by incorporating an easy-to-use semantic layer within its lakehouse platform. This feature allows users to organize and document data from all sources into a single, coherent layer, facilitating data discovery. Beyond organization, Dremio enables robust data governance through role-based, column-based, and row-based access controls, ensuring users can only access the data they are permitted to view. This semantic layer enhances collaboration across data teams, offering a unified access point that supports the implementation of data-centric architectures like data mesh. By streamlining data access and collaboration, Dremio not only makes data more discoverable and understandable but also ensures a secure and controlled data environment, aligning with best practices in data management and governance. 1. Hybrid Architecture Many contemporary data tools focus predominantly on cloud-based data, sidelining the vast reserves of on-premise data that cannot leverage these modern solutions. Dremio, however, stands out by offering the capability to access on-premise data sources in addition to cloud data. This flexibility allows Dremio to unify on-premise and cloud data sources, facilitating seamless migrations between different systems. With Dremio, organizations can enhance their on-premise data by integrating it with the wealth of data available in cloud data marketplaces, all without the need for data movement. This approach not only broadens the scope of data resources available to businesses but also enables a more integrated and comprehensive data strategy, accommodating the needs of organizations with diverse data environments. Conclusion Apache Iceberg and Dremio are spearheading a transformative shift in data management and analysis. Apache Iceberg's innovative features, such as partition evolution, hidden partitioning, advanced versioning, and open-source culture, set it apart in the realm of data table formats, offering flexibility, efficiency, and a collaborative development environment. On the other hand, Dremio's data lakehouse platform leverages these strengths and further enhances the data management experience with its integrated SQL query engine, semantic layer, and unique features like Reflections and the C3 Columnar Cloud Cache. By providing a unified platform that addresses the challenges of both on-premise and cloud data, Dremio eliminates the complexity and fragmentation often associated with data analytics. Its ability to streamline data processing, ensure robust data governance, and facilitate seamless integration across diverse data sources makes it an invaluable asset for organizations aiming to leverage their data for insightful analytics and informed decision-making. Together, Apache Iceberg and Dremio not only offer a robust foundation for data management but also embody the future of data analytics, where accessibility, efficiency, and collaboration are key. Whether you're a data engineer looking to optimize data storage and retrieval or a data analyst seeking intuitive and powerful data exploration tools, this combination presents a compelling solution in the ever-evolving landscape of data technology. Also published . here

Data Potential: 10 Reasons Apache Iceberg and Dremio Should Be Part of Your Data Lakehouse Strategy

designed for data lakehouse architectures, enabling the organization of data on data lakes like tables found in traditional databases and data warehouses. This innovative table format provides a crucial abstraction layer, allowing users to leverage database-like features on their data lakes. Its key features are ACID transactions, which ensure data integrity and consistency, time travel capabilities allowing users to access historical data snapshots, and robust table evolution mechanisms for managing partitions and schema changes. By integrating these functionalities, transforms data lakes into more structured and manageable environments, facilitating advanced data analytics and management tasks. Apache Iceberg is an open-source table format Apache Iceberg The Role of Catalogs in Apache Iceberg The catalog mechanism is a cornerstone in the functionality of Apache Iceberg tables, providing a crucial layer of organization and accessibility, even though the specifics of its implementation are beyond the Iceberg specification. A catalog in Iceberg serves as a registry for tables, tracking Iceberg tables to ensure they are discoverable by compatible tools, thereby facilitating seamless integration and usage. Moreover, catalogs are instrumental in maintaining a consistent view of the data, which is essential for the integrity and reliability of ACID transactions. By acting as the source of truth, catalogs enable concurrent transactions to reference them and . This mechanism is vital for maintaining data consistency and ensuring that the system provides ACID guarantees, thereby enhancing the robustness and reliability of data operations within the Iceberg ecosystem. ascertain the status of other ongoing transactions, effectively determining if another transaction was committed while theirs was in progress Challenges with Catalogs and Choosing the Right Catalog For you When selecting a catalog for Apache Iceberg, several key factors should guide your decision: compatibility with your current tools, the additional functionalities or integrations the catalog offers, and its maintainability. It’s crucial to choose only one catalog for managing your tables because, upon the completion of a transaction, only the active catalog is updated. Utilizing multiple catalogs could result in them referencing outdated table states, leading to consistency issues. If there is an absolute need to employ multiple catalogs, a feasible approach is to designate a single catalog for write operations while others are used solely for reading. However, this setup demands the implementation of custom systems to synchronize the read-only catalogs with the primary to ensure they reflect the most current table state, maintaining consistency to the greatest extent possible. Service and File-System Catalogs The distinction between a catalog in Apache Iceberg is fundamental to understanding their operational dynamics and use cases. Service catalogs, which constitute the majority, involve a running service that can be either self-managed or cloud-managed. These catalogs utilize a backing store to maintain all references to Iceberg tables, with locking mechanisms in place to enforce ACID guarantees. This setup ensures that when a table is modified, the catalog updates references accurately, preventing conflicting changes from being committed. service catalog and a file-system On the other hand, the “Hadoop Catalog” represents a file-system catalog that is compatible with any storage system. Unlike service catalogs, the Hadoop Catalog does not rely on a backing store but instead uses a file named “version-hint.text” on the file system to track the latest version of the table. This file must be updated whenever the table changes. However, since not all storage systems provide the same level of atomicity and consistency in file replacement, this method can lead to potential inconsistencies, especially in environments with high concurrency. Therefore, while the Hadoop Catalog might be suitable for evaluating Iceberg’s capabilities, it is generally not recommended for production use due to these potential consistency issues. A tour of Apache Iceberg Catalogs In the following section, we will delve into the diverse range of currently existing catalogs available within the Apache Iceberg ecosystem. Each catalog offers unique features, integrations, and compatibility with different data storage systems and processing engines. Understanding the nuances of these catalogs is crucial for architects and developers to make informed decisions that align with their specific data infrastructure needs and operational goals. We’ll explore a variety of catalogs, including those that are widely adopted in the industry as well as emerging options, highlighting their respective advantages, use cases, and Nessie that extends beyond the traditional catalog capabilities in the Apache Iceberg ecosystem, introducing . This catalog not only tracks table metadata but also allows users to capture commits at a holistic level, enabling advanced operations such as multi-table transactions, rollbacks, branching, and tagging. These features provide a new layer of flexibility and control over data changes, resembling version control systems in software development. Nessie is an innovative open-source catalog git-like features to data management Nessie can be either self-managed or cloud-managed, with the latter option available through the Dremio Lakehouse Platform. Dremio integrates Nessie into its , offering a seamless experience that includes automated table optimization alongside Nessie’s robust cataloging capabilities. This integration underscores Nessie’s versatility and its potential to enhance data governance and management in modern data architectures. Dremio Cloud product Hive The Hive catalog offers a seamless integration pathway for organizations already utilizing Hive in their data architectures, allowing them to leverage their existing Hive metastore as an Apache Iceberg catalog. This integration facilitates a smooth transition to Iceberg’s advanced features while maintaining compatibility with the existing Hive ecosystem. By using the Hive catalog, users can avoid the redundancy of maintaining separate metadata stores, streamlining their data management processes. However, for those not currently using Hive, adopting the Hive catalog would necessitate setting up and running a Hive metastore service. This requirement introduces an additional layer of infrastructure that might be better served using an option with additional features. REST The REST catalog represents a unique approach in the Apache Iceberg ecosystem, serving not as a standalone catalog but as a universal interface that can be adapted for any catalog type. It is based on an OPEN API specification that can be implemented in any programming language, provided that the specified endpoints are adhered to. This flexibility allows for the creation of custom catalogs tailored to specific use cases, enabling developers and organizations to contribute new catalog types to the community without the need to develop bespoke support for a myriad of engines and tools. Among the catalogs utilizing this specification are Tabular, which offers a “headless warehouse” solution; Unity Catalog from Databricks, which primarily manages Delta Lake tables but also provides Iceberg table access through its UniFormat feature; and Gravitino, an emerging open-source catalog project. The community’s vision is that all catalogs will eventually interface through this REST specification, simplifying tool integration by requiring only a single interface. However, it’s important to note that the specification is still evolving, with version 3 under discussion and development, which is anticipated to introduce additional endpoints for greater extensibility and the incorporation of custom behaviors. AWS Glue The AWS Glue catalog is an integral component of the AWS ecosystem, providing a fully managed catalog service that integrates seamlessly with other AWS tools such as Redshift and AWS Athena. As a native AWS service, it offers a streamlined experience for users deeply embedded in the AWS infrastructure, ensuring compatibility and optimized performance across AWS services. A notable feature of the AWS Glue catalog is its support for auto-compaction of tables through the AWS Lake Formation service, enhancing data management and optimization. While the AWS Glue catalog is an excellent choice for those committed to the AWS platform, organizations operating in on-premises environments or across multiple cloud providers might benefit from considering a cloud-agnostic catalog to ensure flexibility and avoid vendor lock-in. Snowflake Catalog The Snowflake Iceberg catalog offers a unique integration, allowing Snowflake to manage Apache Iceberg tables that are stored externally on your storage system. This integration aligns with Snowflake’s robust data management capabilities while offering the cost benefits of utilizing external storage. However, there are limitations to consider: all table creation, insertions, updates, and deletions must be conducted within Snowflake, as the Snowflake SDK currently only supports reading operations from Spark. While this setup allows users to leverage some cost savings by storing tables outside of Snowflake, it comes with a trade-off in terms of flexibility. Users do not have access to the full range of open-ecosystem tools for managing Snowflake-managed Iceberg tables, which could be a significant consideration for organizations that rely on a diverse set of data tools and platforms. LakeFS Catalog Initially, there was a compatibility issue between LakeFS, a file-versioning solution, and Apache Iceberg due to a fundamental difference in their design: Iceberg relies on absolute paths in its metadata to reference files, whereas LakeFS uses relative paths to manage different file versions. To bridge this gap, LakeFS introduced its own custom catalog, allowing it to integrate with Apache Iceberg. However, as with any custom catalog, there’s a dependency on engine support, which, at the time of writing, appears to be limited to Apache Spark. While versioning is a powerful feature for data management, users looking to leverage versioning for their Iceberg tables might find the built-in table versioning features of Iceberg or the catalog-level versioning offered by Nessie to be more universally compatible and supported options, especially when considering broader ecosystem integration beyond LakeFS’s Iceberg catalog. Other As the Apache Iceberg community evolves, there’s a noticeable shift away from certain catalogs, primarily due to concerns like maintenance challenges or inconsistent implementations. Two such catalogs are the JDBC catalog and the DynamoDB catalog. The JDBC catalog, which enabled any JDBC-compatible database to function as an Iceberg catalog, is seeing reduced usage. This decline is likely due to the complexities and variances in how different databases implement JDBC, potentially leading to inconsistencies in catalog behavior. Similarly, the DynamoDB catalog, initially used in the early stages of AWS support for Iceberg, is also falling out of favor. The community’s pivot away from these catalogs underscores a broader trend towards more robust, consistently supported, and feature-rich catalog options that align with the evolving needs and standards of Iceberg users and developers. Conclusion Apache Iceberg stands as a transformative force in the data lakehouse landscape, offering a structured and efficient way to manage data on data lakes with features traditionally reserved for databases and data warehouses. The journey through the diverse world of Apache Iceberg catalogs highlights the importance of these components in ensuring data accessibility, consistency, and robust transactional support. From the integration-friendly Hive catalog to the innovative Nessie catalog that brings git-like versioning to data, each catalog serves a unique purpose and caters to different architectural needs and preferences. As we’ve explored, choosing the right catalog is crucial, balancing factors like compatibility, functionality, and the specific context of your data ecosystem. Whether you’re deeply embedded in the AWS infrastructure, leveraging the AWS Glue catalog, or exploring the versioning capabilities of LakeFS or Nessie, the decision should align with your strategic objectives and operational requirements. The evolution away from certain catalogs, like the JDBC and DynamoDB catalogs, underscores the community’s drive towards more reliable, feature-rich, and consistent catalog implementations. This shift is a testament to the ongoing maturation of the Iceberg ecosystem and its users’ commitment to adopting practices and tools that enhance data reliability, scalability, and manageability. As Apache Iceberg continues to evolve, so too will its ecosystem of catalogs, each adapting to the emerging needs of data professionals seeking to harness the full potential of their data lakehouses. Embracing these tools and understanding their nuances will empower organizations to build more resilient, flexible, and efficient data architectures, paving the way for advanced analytics and data-driven decision-making. Also published . here

Navigating Apache Iceberg: A Deep Dive into Catalogs & Their Role in Data Lakehouse Architectures

The dark web is a shadowy online marketplace where victims are held captive by cyber extortionists, and stolen data is traded. It is hidden away in the shadows of the internet. This was the reality of LockBit's dark web domain, a platform the notorious ransomware gang used to extort businesses and organizations worldwide. According to the Department of Justice, LockBit earned itself in revenue from shady data deals and ransom payments. But luckily, after global cooperation, this virtual den of evil has been shut down, a major victory for international law enforcement. 2,000 victims and made over $120 million Unveiling LockBit's Dark Schemes Until recently, LockBit was a prominent player in the RaaS (Ransomware-as-a-Service) landscape. It is a ransomware gang that has plagued the cybersecurity landscape for years. Their ransomware variant, known for its “double extortion” tactic of encrypting data and threatening to leak it online, has caused billions of dollars in losses and disrupted operations for countless victims. Double extortion is a cruel and calculated strategy designed to squeeze maximum ransom payments from their victims. Let’s look at how this devil works! Initial Infection and Data Exfiltration The first phase of LockBit's attack involves infiltrating the victim's network through various methods, often exploiting vulnerabilities in outdated software or tricking employees into clicking malicious links. Once inside, they silently crawl through the system, identifying and exfiltrating sensitive data. This stolen treasure trove could include financial records, customer information, intellectual property, internal documents, and personally identifiable information (PII). Imagine their victim's horror as LockBit siphons away these critical files, leaving them vulnerable and exposed. Data Encryption With the stolen data securely tucked away, LockBit delivers the next blow: widespread data encryption. They deploy their malicious software, scrambling the victim's essential files, and rendering them inaccessible and unusable. This digital lockdown brings operations to a screeching halt, causing significant disruption and panic. Ransom Demand But LockBit doesn't stop there. They twist the knife further by brandishing the stolen data as a weapon. The ransom note is a cruel ultimatum that clearly outlines the situation: pay the ransom or face the public exposure of your sensitive information. This nightmarish scenario threatens to shatter the victim's reputation. Naturally, it’s highly embarrassing for any individual. But for a company, it could also result in financial losses from regulatory fines for not complying with safety guidelines, legal repercussions for data breaches and privacy violations, and irreparable damage to customer trust. The Threat of Exposure Faced with this double extortion dilemma, victims are caught in a pressure cooker. Even if they have backups to restore their encrypted data, the looming threat of public humiliation makes the decision agonizing. This cruel tactic has proven highly effective for LockBit, forcing many victims to succumb to their ransom demands. Here are some notable examples of LockBit's past attacks: June 2023: LockBit demanded a $70 million ransom from TSMC, a major Taiwanese semiconductor manufacturer. July 2023: The group crippled operations at the Port of Nagoya in Japan, which handles 10% of the country's trade, by launching a ransomware attack. October 2023: LockBit claimed to have stolen sensitive data from Boeing, although the company did not confirm the breach. The group targeted critical infrastructure, healthcare, education, and government agencies, demonstrating their widespread reach. Taking Down the Command and Control System Imagine a multi-headed hydra lurking in the murky depths of the internet, each head representing a different facet of nefarious operation. This mythical beast communicated with its victims, brandished stolen data like trophies, and demanded ransoms through its domain on the dark web. LockBit's The LockBit monster (not to be confused with the Loch Ness monster) has digitally terrorized individuals, multinational organizations, and even hospitals for over four years. But in a worthy of a Greek hero, a global alliance of law enforcement agencies joined forces to sever the hydra's heads. coup de grâce In a collaborative effort dubbed Operation Cronos, the , the UK's , and law enforcement agencies from Australia, Canada, New Zealand, and Europe joined forces to seize control of LockBit's dark web infrastructure. FBI National Crime Agency (NCA) This decisive action effectively dismantled the gang's online extortion platform, disrupting their ability to communicate with victims, showcase stolen data, and collect ransom payments. Europol arrested two alleged, unnamed operatives in Poland and Ukraine, while the US has indicted Russian men Ivan Gennadievich Kondratiev and Artur Sungatov for deploying LockBit against various American organizations. The operation dealt a significant blow to the cybercriminal group, demonstrating the collective power of international cooperation in combating cybercrime. But how did this takedown come about, and what does it mean for the fight against ransomware? Understanding Operation Cronos The takedown of LockBit's dark website involved a meticulous and multifaceted approach by law enforcement agencies. The director general of the NCA, Graeme Biggar, said after the operation's success, “We have hacked the hackers; taken control of their infrastructure, seized their source code, and obtained keys that will help victims decrypt their systems.” Here’s a closer look at what that entailed: International law enforcement agencies collaborated to infiltrate LockBit's network and gather intelligence on their operations by monitoring their activities and identifying vulnerabilities in their infrastructure. Hacking the Hackers: Authorities strategically disrupted communication channels between LockBit and their affiliates, hindering their ability to coordinate attacks and manage extortion operations. Taking Control of Infrastructure: In a coordinated effort, law enforcement agencies from various countries seized control of LockBit's dark web domain. This involved taking down the website and preventing further access by the gang or their victims. Seizing Source Code: The seized infrastructure provided valuable evidence for ongoing investigations, potentially leading to the identification and apprehension of individual members of the LockBit gang. Securing Evidence: Through the evidence on the website, law enforcement is working to identify victims who may have interacted with the website and assist them in recovering their data. Obtaining Decryption Keys: Continuing the Fight While the takedown of LockBit's dark website represents a significant victory, the fight against cybercrime is ongoing. New threats are constantly emerging, and ransomware remains a major concern for businesses and organizations. We have gained a few key takeaways from this event: Operation Cronos highlights the importance of collaboration between law enforcement agencies across the globe in dismantling cybercriminal operations and protecting victims. International cooperation is essential: Organizations must prioritize robust cybersecurity measures, including regular software updates and comprehensive backup and recovery plans, to minimize their vulnerability to ransomware attacks. Cybersecurity vigilance remains critical: While this takedown is a positive development, it's essential to stay informed about evolving threats, adapt cybersecurity strategies accordingly, and foster continuous collaboration to create a more secure digital environment. The fight against cybercrime is a marathon, not a sprint: Looking Ahead to A Brighter Future for Cybersecurity The takedown of LockBit's dark web lair is like evicting a particularly nasty troll from the internet's underbelly. It's a positive step, but let's not break out the celebratory cupcakes just yet. This is just one skirmish in the ongoing war against cybercrime, and plenty of digital dragons are still lurking out there. However, there's no need to don your tinfoil hats and retreat to a Faraday cage. By staying informed, adopting robust cybersecurity practices, and working together like a well-oiled international task force of digital knights, we can make the internet safer for everyone. Breaking Down the Potential Long-Term Impacts While the immediate impact of Operation Cronos is the disruption of LockBit's operations, the long-term consequences could be far-reaching. By dismantling LockBit's infrastructure and potentially identifying key members, law enforcement could disrupt the RaaS ecosystem, making it more difficult for other ransomware groups to operate. The successful takedown could serve as a deterrent to other cybercriminal groups, discouraging them from using similar tactics. Best of all, with access to seized data, law enforcement can potentially assist victims in recovering stolen information and mitigating the impact of the attacks. Exploring Challenges and Considerations It's important to acknowledge that the fight against cybercrime is complex and constantly evolving. While Operation Cronos is a significant victory, several challenges remain: Cybercriminals constantly adapt their tactics to evade detection and bypass security measures. Law enforcement and cybersecurity professionals must stay ahead of the curve by continuously learning and adapting their strategies. Evolving tactics: Attributing cyberattacks to specific individuals or groups can be challenging, and international cooperation is crucial for successful prosecution. For instance, it’s going to be difficult for the US to prosecute Russians like Kondratiev, especially because there is no US-Russia extradition agreement. Attribution and Prosecution: The dark web provides a haven for cybercriminals to operate with some degree of anonymity. Law enforcement agencies need to develop innovative methods to effectively investigate and disrupt activities on these hidden corners of the internet. The Dark Web: Final Thoughts The takedown of LockBit's dark website is a significant development in the fight against cybercrime. It demonstrates how international cooperation among law enforcement agencies can protect citizens and businesses from malicious actors. However, this is just one battle, and the fight against cybercrime is a full-scale war. But with continued vigilance, collaboration, and a healthy dose of digital hygiene, we can create a future where browsing the internet feels less like walking through a minefield and more like strolling through a virtual garden.

LockBit's Lair Gets Locked Down: FBI and Allies Take Down Ransomware Gang's Website

How are you, hacker?
🪐 has got you covered with fresh content from our trending stories of the day! Set email preference . Want to know what's trending right now?: The Techbeat by HackerNoon here Product Discovery in B2B and B2B2C Environments: A Guide for Product Managers By [ 5 Min read ]
Product discovery is a key stage in the product development lifecycle. In B2B and B2C businesses, this process has its nuances, which I cover in this article. @dashadobrego Read More. Octopus Network Unveils Omnity, Pioneering a Fully Decentralized Cross-Chain World By [ 2 Min read ]
Octopus Network announces the upcoming launch of Omnity, a groundbreaking product designed to enhance cross-chain transactions @pressreleases Read More. LanceDB: Your Trusted Steed in the Duel Against Data Complexity By [ 8 Min read ]
There are many ways to build on the foundation offered in this tutorial to create performant, scalable and future-proofed ML/AI architectures. @minio Read More. The Principles to Keep In Mind When Building a Modern Datalake for Your AI Infrastructure By [ 5 Min read ]
The AI game is about performance at scale, and this requires the right foundation. Here's how to be smart when building a modern datalake. @minio Read More. What Are Wallet Drainers? How to Protect Yourself From Them! By [ 7 Min read ]
Learn about wallet drainers, how to detect and respond to compromises, and the role of Wallet Rescue by Hackless in safeguarding the crypto assets. @hackless Read More. Understanding Vulnerabilities and Safeguards in Blockchain Oracles By [ 2 Min read ]
This Blockchain Oracle Summit break down offers key insights into the vulnerabilities and safeguards in the realm of blockchain oracles. @oraclesummit Read More. Headset Reality Wars: Meta @ $1B Quarterly VR Revenue & Apple Vision Pro Sells 200k Units in 10 Days By [ 2 Min read ]
Reality Labs, the VR subsidiary of Meta, passed $1B in Q4 VR Revenue, according to Meta’s earning call. Apple Vision Pro sold 200k units in its first ten days. @david Read More. A Step-By-Step Guide For Implementing OKRs In Your Scaling Startup By [ 6 Min read ]
An OKR has two parts: the objective, your goal, and the key results, what success looks like. @vvmrk Read More. Improving Testing Algorithms: Mathematical Approaches in Software Testing By [ 7 Min read ]
Test design, Code coverage, MC/DC, Boolean algebra, Pairwise testing, Combinatorial testing, Orthogonal arrays, System states @shad0wpuppet Read More. Cybersecurity Tips: Vulnerability Scanners Essentials By [ 6 Min read ]
Cybersecurity Vulnerability Scanners Essentials, OWASP ZAP, Burp Suite, Nessus, Sn1per, Metasploit, SQLMap. @shad0wpuppet Read More. Cybersecurity Essentials: Practical Web App Security Testing Tips for QA Engineers By [ 10 Min read ]
Cybersecurity for QA - web app security: XSS, Header Injections, CSRF, RCE, Command Injection, Web Parameter Tampering, CORS, Content Security Policy (CSP) @shad0wpuppet Read More. How to Use AI and PDF Services to Automate Document Summaries By [ 8 Min read ]
My three-page PDF is now one simple paragraph. You can imagine how useful this would be for organizations with millions of documents. @raymondcamden Read More. Why Open Source Language Models Are True “Open AI” By [ 4 Min read ]
H2O.ai's Danube is the latest in a series of open-source language models. @FrederikBussler Read More. Tech Company News Data Dump on HuggingFace: 7M Most Cited Posts About 3k Most Valued Tech Companies By [ 2 Min read ]
HackerNoon curated and open sourced the internet's most cited 7M+ tech company news articles and blog posts about the 3k+ most valuable tech companies. @david Read More. Timeboxing: How I Plan My Day (as a Product Manager) By [ 2 Min read ]
Timeboxing changed the way I plan my days (and even months). I get more of the right 'stuff' done with this method than I ever did before. @alexdebecker Read More. Dione Protocol Shines as Crypto Winter Thaws: Paving the Way for Green Energy Revolution By [ 7 Min read ]
As the cream rises to the top, Dione Protocol is poised to shine, leveraging this revitalized landscape to drive growth and deliver on the promise of blockchain @dioneprotocol Read More. I Built a Platform to Help Users Practice Programming Challenges Guided by AI By [ 6 Min read ]
Walking  through the process of building a platform leveraging AI to help users practice for interviews; integrating feedback from the first few live user tests @emmanuels Read More. The Top 13 Trends in 2024: AI Predictions By [ 12 Min read ]
Read our VIRAL 70k-view Medium article "AI predictions: Top 13 AI trends for 2024". A comprehensive guide to the future of artificial intelligence. @pragmaticcoders Read More. Tech-Gate.org Racks Up Over 1000 DMCA Copyright Infringements By [ 5 Min read ]
Tech-Gate.org, apparent operated and published under the name Bourbiza Mohamed, has been under fire for this rampant copyright infringement site. @technologynews Read More. A Year Since ChatGPT Launch: Do Content Creators Really Need to Fear AI? By [ 6 Min read ]
A closer look at the impact of ChatGPT on writing jobs and the content industry. 🧑‍💻 What happened in your world this week? It's been said that , , . Feeling stuck? We got you covered ⬇️⬇️⬇️ We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.
See you on Planet Internet! With love,
The HackerNoon Team ✌️ @deepikapundora Read More. writing can help consolidate technical knowledge establish credibility and contribute to emerging community standards ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME

The TechBeat: Product Discovery in B2B and B2B2C Environments: A Guide for Product Managers (2/12/2024)

How are you, hacker?
🪐 has got you covered with fresh content from our trending stories of the day! Set email preference . Want to know what's trending right now?: The Techbeat by HackerNoon here Octopus Network Unveils Omnity, Pioneering a Fully Decentralized Cross-Chain World By [ 2 Min read ]
Octopus Network announces the upcoming launch of Omnity, a groundbreaking product designed to enhance cross-chain transactions @pressreleases Read More. LanceDB: Your Trusted Steed in the Duel Against Data Complexity By [ 8 Min read ]
There are many ways to build on the foundation offered in this tutorial to create performant, scalable and future-proofed ML/AI architectures. @minio Read More. Understanding Vulnerabilities and Safeguards in Blockchain Oracles By [ 2 Min read ]
This Blockchain Oracle Summit break down offers key insights into the vulnerabilities and safeguards in the realm of blockchain oracles. @oraclesummit Read More. What Are Wallet Drainers? How to Protect Yourself From Them! By [ 7 Min read ]
Learn about wallet drainers, how to detect and respond to compromises, and the role of Wallet Rescue by Hackless in safeguarding the crypto assets. @hackless Read More. The Principles to Keep In Mind When Building a Modern Datalake for Your AI Infrastructure By [ 5 Min read ]
The AI game is about performance at scale, and this requires the right foundation. Here's how to be smart when building a modern datalake. @minio Read More. A Step-By-Step Guide For Implementing OKRs In Your Scaling Startup By [ 6 Min read ]
An OKR has two parts: the objective, your goal, and the key results, what success looks like. @vvmrk Read More. Headset Reality Wars: Meta @ $1B Quarterly VR Revenue & Apple Vision Pro Sells 200k Units in 10 Days By [ 2 Min read ]
Reality Labs, the VR subsidiary of Meta, passed $1B in Q4 VR Revenue, according to Meta’s earning call. Apple Vision Pro sold 200k units in its first ten days. @david Read More. Building a Unicorn: The inDrive Tech Journey from Local Startup to Global Phenomenon By [ 10 Min read ]
Michil Androsov shares an insider's perspective on how a simple idea from the depths of Siberia grew into a global ride-hailing phenomenon. @michil Read More. 10 Tips to Take Your ChatGPT Prompts to the Next Level By [ 11 Min read ]
Maximize your ChatGPT experience with 10 expert tips for crafting precise prompts and queries, enhancing interaction quality. @morganmsk Read More. Cybersecurity Tips: Vulnerability Scanners Essentials By [ 6 Min read ]
Cybersecurity Vulnerability Scanners Essentials, OWASP ZAP, Burp Suite, Nessus, Sn1per, Metasploit, SQLMap. @shad0wpuppet Read More. Improving Testing Algorithms: Mathematical Approaches in Software Testing By [ 7 Min read ]
Test design, Code coverage, MC/DC, Boolean algebra, Pairwise testing, Combinatorial testing, Orthogonal arrays, System states @shad0wpuppet Read More. Cybersecurity Essentials: Practical Web App Security Testing Tips for QA Engineers By [ 10 Min read ]
Cybersecurity for QA - web app security: XSS, Header Injections, CSRF, RCE, Command Injection, Web Parameter Tampering, CORS, Content Security Policy (CSP) @shad0wpuppet Read More. Why Open Source Language Models Are True “Open AI” By [ 4 Min read ]
H2O.ai's Danube is the latest in a series of open-source language models. @FrederikBussler Read More. Tech Bro, Crypto Bro, and NFT Bro - The Evolution of Identity in the Digital World By [ 2 Min read ]
Let's find out who crypto, tech, and NFT bros are, where they came from, and why they are subjected to ridicule online. Hold tight, our journey will be awesome! @cryptobro Read More. Dione Protocol Shines as Crypto Winter Thaws: Paving the Way for Green Energy Revolution By [ 7 Min read ]
As the cream rises to the top, Dione Protocol is poised to shine, leveraging this revitalized landscape to drive growth and deliver on the promise of blockchain @dioneprotocol Read More. I Built a Platform to Help Users Practice Programming Challenges Guided by AI By [ 6 Min read ]
Walking  through the process of building a platform leveraging AI to help users practice for interviews; integrating feedback from the first few live user tests @emmanuels Read More. The Top 13 Trends in 2024: AI Predictions By [ 12 Min read ]
Read our VIRAL 70k-view Medium article "AI predictions: Top 13 AI trends for 2024". A comprehensive guide to the future of artificial intelligence. @pragmaticcoders Read More. Tech Company News Data Dump on HuggingFace: 7M Most Cited Posts About 3k Most Valued Tech Companies By [ 2 Min read ]
HackerNoon curated and open sourced the internet's most cited 7M+ tech company news articles and blog posts about the 3k+ most valuable tech companies. @david Read More. Timeboxing: How I Plan My Day (as a Product Manager) By [ 2 Min read ]
Timeboxing changed the way I plan my days (and even months). I get more of the right 'stuff' done with this method than I ever did before. @alexdebecker Read More. Tech-Gate.org Racks Up Over 1000 DMCA Copyright Infringements By [ 5 Min read ]
Tech-Gate.org, apparent operated and published under the name Bourbiza Mohamed, has been under fire for this rampant copyright infringement site. 🧑‍💻 What happened in your world this week? It's been said that , , . Feeling stuck? We got you covered ⬇️⬇️⬇️ We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.
See you on Planet Internet! With love,
The HackerNoon Team ✌️ @technologynews Read More. writing can help consolidate technical knowledge establish credibility and contribute to emerging community standards ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME

The TechBeat: Octopus Network Unveils Omnity, Pioneering a Fully Decentralized Cross-Chain World (2/10/2024)

How are you, hacker?
🪐 has got you covered with fresh content from our trending stories of the day! Set email preference . Want to know what's trending right now?: The Techbeat by HackerNoon here What Are Wallet Drainers? How to Protect Yourself From Them! By [ 7 Min read ]
Learn about wallet drainers, how to detect and respond to compromises, and the role of Wallet Rescue by Hackless in safeguarding the crypto assets. @hackless Read More. Understanding Vulnerabilities and Safeguards in Blockchain Oracles By [ 2 Min read ]
This Blockchain Oracle Summit break down offers key insights into the vulnerabilities and safeguards in the realm of blockchain oracles. @oraclesummit Read More. Octopus Network Unveils Omnity, Pioneering a Fully Decentralized Cross-Chain World By [ 2 Min read ]
Octopus Network announces the upcoming launch of Omnity, a groundbreaking product designed to enhance cross-chain transactions @pressreleases Read More. LanceDB: Your Trusted Steed in the Duel Against Data Complexity By [ 8 Min read ]
There are many ways to build on the foundation offered in this tutorial to create performant, scalable and future-proofed ML/AI architectures. @minio Read More. The System Design Cheat Sheet: Cache By [ 9 Min read ]
The system design cheat sheet for caching is used to reduce latency and improve the efficiency of data retrieval across the distributed system. @gavr Read More. A Step-By-Step Guide For Implementing OKRs In Your Scaling Startup By [ 6 Min read ]
An OKR has two parts: the objective, your goal, and the key results, what success looks like. @vvmrk Read More. Building a Unicorn: The inDrive Tech Journey from Local Startup to Global Phenomenon By [ 10 Min read ]
Michil Androsov shares an insider's perspective on how a simple idea from the depths of Siberia grew into a global ride-hailing phenomenon. @michil Read More. 10 Tips to Take Your ChatGPT Prompts to the Next Level By [ 11 Min read ]
Maximize your ChatGPT experience with 10 expert tips for crafting precise prompts and queries, enhancing interaction quality. @morganmsk Read More. The Principles to Keep In Mind When Building a Modern Datalake for Your AI Infrastructure By [ 5 Min read ]
The AI game is about performance at scale, and this requires the right foundation. Here's how to be smart when building a modern datalake. @minio Read More. Headset Reality Wars: Meta @ $1B Quarterly VR Revenue & Apple Vision Pro Sells 200k Units in 10 Days By [ 2 Min read ]
Reality Labs, the VR subsidiary of Meta, passed $1B in Q4 VR Revenue, according to Meta’s earning call. Apple Vision Pro sold 200k units in its first ten days. @david Read More. The Noonification: A Deep Dive Into Semantic Segmentation Evaluation Metrics (1/28/2024) By [ 2 Min read ]
1/28/2024: Top 5 stories on the HackerNoon homepage! @noonification Read More. Cybersecurity Tips: Vulnerability Scanners Essentials By [ 6 Min read ]
Cybersecurity Vulnerability Scanners Essentials, OWASP ZAP, Burp Suite, Nessus, Sn1per, Metasploit, SQLMap. @shad0wpuppet Read More. Tech Bro, Crypto Bro, and NFT Bro - The Evolution of Identity in the Digital World By [ 2 Min read ]
Let's find out who crypto, tech, and NFT bros are, where they came from, and why they are subjected to ridicule online. Hold tight, our journey will be awesome! @cryptobro Read More. Improving Testing Algorithms: Mathematical Approaches in Software Testing By [ 7 Min read ]
Test design, Code coverage, MC/DC, Boolean algebra, Pairwise testing, Combinatorial testing, Orthogonal arrays, System states @shad0wpuppet Read More. Why Open Source Language Models Are True “Open AI” By [ 4 Min read ]
H2O.ai's Danube is the latest in a series of open-source language models. @FrederikBussler Read More. Cybersecurity Essentials: Practical Web App Security Testing Tips for QA Engineers By [ 10 Min read ]
Cybersecurity for QA - web app security: XSS, Header Injections, CSRF, RCE, Command Injection, Web Parameter Tampering, CORS, Content Security Policy (CSP) @shad0wpuppet Read More. 4 AI Side Hustles in 2024: Earn Big from Home By [ 5 Min read ]
Can you make money from AI? Yes, you can! Here are some side hustles to look into today! @lynnxyz Read More. Microsoft CEO and Chief Economist Disagree on Regulation Timing for New Technologies - WEF Davos By [ 3 Min read ]
Today at the WEF annual meeting in Davos, Switzerland, Schwab asked Nadella what rebuilding trust meant to him in the context of the tech industry. @thesociable Read More. I Built a Platform to Help Users Practice Programming Challenges Guided by AI By [ 6 Min read ]
Walking  through the process of building a platform leveraging AI to help users practice for interviews; integrating feedback from the first few live user tests @emmanuels Read More. Dione Protocol Shines as Crypto Winter Thaws: Paving the Way for Green Energy Revolution By [ 7 Min read ]
As the cream rises to the top, Dione Protocol is poised to shine, leveraging this revitalized landscape to drive growth and deliver on the promise of blockchain 🧑‍💻 What happened in your world this week? It's been said that , , . Feeling stuck? We got you covered ⬇️⬇️⬇️ We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.
See you on Planet Internet! With love,
The HackerNoon Team ✌️ @dioneprotocol Read More. writing can help consolidate technical knowledge establish credibility and contribute to emerging community standards ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME

The TechBeat: What Are Wallet Drainers? How to Protect Yourself From Them! (2/8/2024)

How are you, hacker?
🪐 has got you covered with fresh content from our trending stories of the day! Set email preference . Want to know what's trending right now?: The Techbeat by HackerNoon here A Deep Dive on Digital Identity: Why You Need to Check Out Genies Traits Framework By [ 9 Min read ]
What if your avatar in the Genies Ecosystem encoded not only your visual representation but also who you are – your personality, quirks, and all? @genies Read More. What Are Wallet Drainers? How to Protect Yourself From Them! By [ 7 Min read ]
Learn about wallet drainers, how to detect and respond to compromises, and the role of Wallet Rescue by Hackless in safeguarding the crypto assets. @hackless Read More. Understanding Vulnerabilities and Safeguards in Blockchain Oracles By [ 2 Min read ]
This Blockchain Oracle Summit break down offers key insights into the vulnerabilities and safeguards in the realm of blockchain oracles. @oraclesummit Read More. Octopus Network Unveils Omnity, Pioneering a Fully Decentralized Cross-Chain World By [ 2 Min read ]
Octopus Network announces the upcoming launch of Omnity, a groundbreaking product designed to enhance cross-chain transactions @pressreleases Read More. LanceDB: Your Trusted Steed in the Duel Against Data Complexity By [ 8 Min read ]
There are many ways to build on the foundation offered in this tutorial to create performant, scalable and future-proofed ML/AI architectures. @minio Read More. The System Design Cheat Sheet: Cache By [ 9 Min read ]
The system design cheat sheet for caching is used to reduce latency and improve the efficiency of data retrieval across the distributed system. @gavr Read More. Building a Unicorn: The inDrive Tech Journey from Local Startup to Global Phenomenon By [ 10 Min read ]
Michil Androsov shares an insider's perspective on how a simple idea from the depths of Siberia grew into a global ride-hailing phenomenon. @michil Read More. Using Witnet to Overcome The Challenges of Developing A Truly Multichain Oracle Network By [ 4 Min read ]
Tomas Ruiz on overcoming the challenges of developing a truly multi-chain oracle network using Witnet. @oraclesummit Read More. A Step-By-Step Guide For Implementing OKRs In Your Scaling Startup By [ 6 Min read ]
An OKR has two parts: the objective, your goal, and the key results, what success looks like. @vvmrk Read More. The Noonification: A Deep Dive Into Semantic Segmentation Evaluation Metrics (1/28/2024) By [ 2 Min read ]
1/28/2024: Top 5 stories on the HackerNoon homepage! @noonification Read More. Cybersecurity Tips: Vulnerability Scanners Essentials By [ 6 Min read ]
Cybersecurity Vulnerability Scanners Essentials, OWASP ZAP, Burp Suite, Nessus, Sn1per, Metasploit, SQLMap. @shad0wpuppet Read More. 10 Tips to Take Your ChatGPT Prompts to the Next Level By [ 11 Min read ]
Maximize your ChatGPT experience with 10 expert tips for crafting precise prompts and queries, enhancing interaction quality. @morganmsk Read More. Product Managers, Designers, and Devs: What Does Their Future Look Like in a World Filled With AI? By [ 6 Min read ]
The predictions for the future of tech jobs and the macro trends that will impact our collective experience @kamilaselig Read More. Improving Testing Algorithms: Mathematical Approaches in Software Testing By [ 7 Min read ]
Test design, Code coverage, MC/DC, Boolean algebra, Pairwise testing, Combinatorial testing, Orthogonal arrays, System states @shad0wpuppet Read More. Cybersecurity Essentials: Practical Web App Security Testing Tips for QA Engineers By [ 10 Min read ]
Cybersecurity for QA - web app security: XSS, Header Injections, CSRF, RCE, Command Injection, Web Parameter Tampering, CORS, Content Security Policy (CSP) @shad0wpuppet Read More. Gamification: A New Era in Workplace Experiences By [ 6 Min read ]
Explore the impact of low employee motivation and the role of enterprise gamification in boosting engagement, eliminating friction, and fostering creativity. @igorpaniuk Read More. Microsoft CEO and Chief Economist Disagree on Regulation Timing for New Technologies - WEF Davos By [ 3 Min read ]
Today at the WEF annual meeting in Davos, Switzerland, Schwab asked Nadella what rebuilding trust meant to him in the context of the tech industry. @thesociable Read More. Tech Bro, Crypto Bro, and NFT Bro - The Evolution of Identity in the Digital World By [ 2 Min read ]
Let's find out who crypto, tech, and NFT bros are, where they came from, and why they are subjected to ridicule online. Hold tight, our journey will be awesome! @cryptobro Read More. 4 AI Side Hustles in 2024: Earn Big from Home By [ 5 Min read ]
Can you make money from AI? Yes, you can! Here are some side hustles to look into today! @lynnxyz Read More. How to Read Tokenomics for Correct Investment By [ 4 Min read ]
Tokenomics - everybody is saying that you should know it if you are going to invest in a project. All about tokenomics. 🧑‍💻 What happened in your world this week? It's been said that , , . Feeling stuck? We got you covered ⬇️⬇️⬇️ We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.
See you on Planet Internet! With love,
The HackerNoon Team ✌️ @dshishov Read More. writing can help consolidate technical knowledge establish credibility and contribute to emerging community standards ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME

The TechBeat: A Deep Dive on Digital Identity: Why You Need to Check Out Genies Traits Framework (2/5/2024)

How are you, hacker?
🪐 has got you covered with fresh content from our trending stories of the day! Set email preference . Want to know what's trending right now?: The Techbeat by HackerNoon here A Deep Dive on Digital Identity: Why You Need to Check Out Genies Traits Framework By [ 9 Min read ]
What if your avatar in the Genies Ecosystem encoded not only your visual representation but also who you are – your personality, quirks, and all? @genies Read More. Using Witnet to Overcome The Challenges of Developing A Truly Multichain Oracle Network By [ 4 Min read ]
Tomas Ruiz on overcoming the challenges of developing a truly multi-chain oracle network using Witnet. @oraclesummit Read More. What Are Wallet Drainers? How to Protect Yourself From Them! By [ 7 Min read ]
Learn about wallet drainers, how to detect and respond to compromises, and the role of Wallet Rescue by Hackless in safeguarding the crypto assets. @hackless Read More. The System Design Cheat Sheet: Cache By [ 9 Min read ]
The system design cheat sheet for caching is used to reduce latency and improve the efficiency of data retrieval across the distributed system. @gavr Read More. Product Managers, Designers, and Devs: What Does Their Future Look Like in a World Filled With AI? By [ 6 Min read ]
The predictions for the future of tech jobs and the macro trends that will impact our collective experience @kamilaselig Read More. Understanding Vulnerabilities and Safeguards in Blockchain Oracles By [ 2 Min read ]
This Blockchain Oracle Summit break down offers key insights into the vulnerabilities and safeguards in the realm of blockchain oracles. @oraclesummit Read More. Building a Unicorn: The inDrive Tech Journey from Local Startup to Global Phenomenon By [ 10 Min read ]
Michil Androsov shares an insider's perspective on how a simple idea from the depths of Siberia grew into a global ride-hailing phenomenon. @michil Read More. The Noonification: A Deep Dive Into Semantic Segmentation Evaluation Metrics (1/28/2024) By [ 2 Min read ]
1/28/2024: Top 5 stories on the HackerNoon homepage! @noonification Read More. LanceDB: Your Trusted Steed in the Duel Against Data Complexity By [ 8 Min read ]
There are many ways to build on the foundation offered in this tutorial to create performant, scalable and future-proofed ML/AI architectures. @minio Read More. Cybersecurity Tips: Vulnerability Scanners Essentials By [ 6 Min read ]
Cybersecurity Vulnerability Scanners Essentials, OWASP ZAP, Burp Suite, Nessus, Sn1per, Metasploit, SQLMap. @shad0wpuppet Read More. Octopus Network Unveils Omnity, Pioneering a Fully Decentralized Cross-Chain World By [ 2 Min read ]
Octopus Network announces the upcoming launch of Omnity, a groundbreaking product designed to enhance cross-chain transactions @pressreleases Read More. Unveiling the Best of 2023: Top Stories, Writers, Tech Categories, and Templates! 📚 By [ 5 Min read ]
We've compiled a 2023 roundup of the top most-read stories, top active writers, top tech categories, and even the top most popular templates. Take a look! @editingprotocol Read More. Improving Testing Algorithms: Mathematical Approaches in Software Testing By [ 7 Min read ]
Test design, Code coverage, MC/DC, Boolean algebra, Pairwise testing, Combinatorial testing, Orthogonal arrays, System states @shad0wpuppet Read More. Cybersecurity Essentials: Practical Web App Security Testing Tips for QA Engineers By [ 10 Min read ]
Cybersecurity for QA - web app security: XSS, Header Injections, CSRF, RCE, Command Injection, Web Parameter Tampering, CORS, Content Security Policy (CSP) @shad0wpuppet Read More. Gamification: A New Era in Workplace Experiences By [ 6 Min read ]
Explore the impact of low employee motivation and the role of enterprise gamification in boosting engagement, eliminating friction, and fostering creativity. @igorpaniuk Read More. A Beginner's Guide to Understanding SQL Window Functions - Part 2 By [ 8 Min read ]
let us explore more advanced SQL concepts. It may sound a bit complicated at first glance, but I will provide simple examples suitable for beginners... @yonatansali Read More. Reverse Proxying — the Backbone of Microservices Architecture By [ 5 Min read ]
Understand how reverse proxies powers almost every service that we use today from monolith to microservices. It is a vital piece of 21st century infrastructure! @infinity Read More. 10 Tips to Take Your ChatGPT Prompts to the Next Level By [ 11 Min read ]
Maximize your ChatGPT experience with 10 expert tips for crafting precise prompts and queries, enhancing interaction quality. @morganmsk Read More. How to Read Tokenomics for Correct Investment By [ 4 Min read ]
Tokenomics - everybody is saying that you should know it if you are going to invest in a project. All about tokenomics. @dshishov Read More. The Best Complex Frontend Architecture: What You Need to Know About Feature-Sliced Design By [ 8 Min read ]
This article discusses the Feature-Sliced Design architecture, as in my opinion, it is the best for complex frontend projects among the available options. 🧑‍💻 What happened in your world this week? It's been said that , , . Feeling stuck? We got you covered ⬇️⬇️⬇️ We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.
See you on Planet Internet! With love,
The HackerNoon Team ✌️ @mmmidas Read More. writing can help consolidate technical knowledge establish credibility and contribute to emerging community standards ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME

The TechBeat: A Deep Dive on Digital Identity: Why You Need to Check Out Genies Traits Framework (2/3/2024)

How are you, hacker?
🪐 has got you covered with fresh content from our trending stories of the day! Set email preference . Want to know what's trending right now?: The Techbeat by HackerNoon here A Deep Dive on Digital Identity: Why You Need to Check Out Genies Traits Framework By [ 9 Min read ]
What if your avatar in the Genies Ecosystem encoded not only your visual representation but also who you are – your personality, quirks, and all? @genies Read More. Using Witnet to Overcome The Challenges of Developing A Truly Multichain Oracle Network By [ 4 Min read ]
Tomas Ruiz on overcoming the challenges of developing a truly multi-chain oracle network using Witnet. @oraclesummit Read More. Product Managers, Designers, and Devs: What Does Their Future Look Like in a World Filled With AI? By [ 6 Min read ]
The predictions for the future of tech jobs and the macro trends that will impact our collective experience @kamilaselig Read More. Unveiling the Best of 2023: Top Stories, Writers, Tech Categories, and Templates! 📚 By [ 5 Min read ]
We've compiled a 2023 roundup of the top most-read stories, top active writers, top tech categories, and even the top most popular templates. Take a look! @editingprotocol Read More. The System Design Cheat Sheet: Cache By [ 9 Min read ]
The system design cheat sheet for caching is used to reduce latency and improve the efficiency of data retrieval across the distributed system. @gavr Read More. The Noonification: A Deep Dive Into Semantic Segmentation Evaluation Metrics (1/28/2024) By [ 2 Min read ]
1/28/2024: Top 5 stories on the HackerNoon homepage! @noonification Read More. Improving Testing Algorithms: Mathematical Approaches in Software Testing By [ 7 Min read ]
Test design, Code coverage, MC/DC, Boolean algebra, Pairwise testing, Combinatorial testing, Orthogonal arrays, System states @shad0wpuppet Read More. Cybersecurity Essentials: Practical Web App Security Testing Tips for QA Engineers By [ 10 Min read ]
Cybersecurity for QA - web app security: XSS, Header Injections, CSRF, RCE, Command Injection, Web Parameter Tampering, CORS, Content Security Policy (CSP) @shad0wpuppet Read More. Cybersecurity Tips: Vulnerability Scanners Essentials By [ 6 Min read ]
Cybersecurity Vulnerability Scanners Essentials, OWASP ZAP, Burp Suite, Nessus, Sn1per, Metasploit, SQLMap. @shad0wpuppet Read More. What Are Wallet Drainers? How to Protect Yourself From Them! By [ 7 Min read ]
Learn about wallet drainers, how to detect and respond to compromises, and the role of Wallet Rescue by Hackless in safeguarding the crypto assets. @hackless Read More. Stand Up for the Champion Startups of the Year! By [ 2 Min read ]
The Startups of the Year 2023 winners are announced! @startups Read More. The Real-Time Internet: Visions of AI-Generated Everything By [ 2 Min read ]
I interview an AI engineering expert on her opinion on Jared Ficklin's vision of the Real-Time Internet, where AI generates applications on demand. @liamshotwell Read More. Gamification: A New Era in Workplace Experiences By [ 6 Min read ]
Explore the impact of low employee motivation and the role of enterprise gamification in boosting engagement, eliminating friction, and fostering creativity. @igorpaniuk Read More. Building a Unicorn: The inDrive Tech Journey from Local Startup to Global Phenomenon By [ 10 Min read ]
Michil Androsov shares an insider's perspective on how a simple idea from the depths of Siberia grew into a global ride-hailing phenomenon. @michil Read More. A Beginner's Guide to Understanding SQL Window Functions - Part 2 By [ 8 Min read ]
let us explore more advanced SQL concepts. It may sound a bit complicated at first glance, but I will provide simple examples suitable for beginners... @yonatansali Read More. The Best Complex Frontend Architecture: What You Need to Know About Feature-Sliced Design By [ 8 Min read ]
This article discusses the Feature-Sliced Design architecture, as in my opinion, it is the best for complex frontend projects among the available options. @mmmidas Read More. How to Use TensorFlow and Cleanvision to Detect Starfish Threats in the Great Barrier Reef By [ 2 Min read ]
Utilizing AI and machine learning, the project employs TensorFlow, Cleanvision, KerasCV, and YOLOv8 to detect harmful starfish in the Great Barrier Reef. @aravindputrevu Read More. Women in Tech: Interview with Anastasia Mironova, Product Designer at WhatsApp London By [ 9 Min read ]
Interview with Anastasia Mironova: sharing her career journey, perspectives on women in tech, and insights into design leadership @anamiro Read More. LLMs for Dummies - Walkthrough Guide and Glossary By [ 4 Min read ]
Feel like an idiot trying to remember the terms in AI? Don't know your inference from your instruction? Here's a collection of common machine learning terms. @reneeeshaw Read More. Reverse Proxying — the Backbone of Microservices Architecture By [ 5 Min read ]
Understand how reverse proxies powers almost every service that we use today from monolith to microservices. It is a vital piece of 21st century infrastructure! 🧑‍💻 What happened in your world this week? It's been said that , , . Feeling stuck? We got you covered ⬇️⬇️⬇️ We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.
See you on Planet Internet! With love,
The HackerNoon Team ✌️ @infinity Read More. writing can help consolidate technical knowledge establish credibility and contribute to emerging community standards ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME

Stories, News & Mentions about NESS

Ness’s Stories on HackerNoon