361 Stories To Learn About Big Data

Let's learn about via these 361 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Big Data /Learn Repo Gather and organize and process insights from large datasets with new computer strategies and technologies 1. An Intro to Resiliency, DHT, and Autonomous Economic Agents According to the paper published by Lokman Rahmani et al., the S/Kademlia distributed hash table (DHT) used by the ACN is resilient against malicious attacks. 2. Pyth and Auros are Bringing Real-Time High-Frequency Data to Blockchain Protocols Auros, a company specialising in algorithmic trading and market making, and Pyth Network will provide access to high-frequency data in real-time. 3. The Top 16 Types of Charts in Data Visualization That You'll Use In the era of information explosion, more and more data piles up. However, these dense data are unfocused and less readable. So we need data visualization to help data to be easily understood and accepted. By contrast, visualization is more intuitive and meaningful, and it is very important to use appropriate charts to visualize data. 4. How to Clean and Verify Address Data 'Without Using Code' Today, data verification has become one of the greatest assets of an organization. 5. Why Data Governance is Vital for Data Management Both data governance and data management workflows are critical to ensuring the security and control of an organization’s most valuable asset-data. 6. How Wikipedia Lost 3 Billion Organic Search Visits To Google in 2019 Since Wikipedia was founded in 2001, people worldwide rely on the online encyclopedia to expand their horizons and read information on just about anything. As true as that is today, however, the site’s traffic trends tell a very different story. 7. Top 10 Open Datasets for Linear Regression On Hacker Noon, I will be sharing some of my best-performing machine learning articles. This listicle on datasets built for regression or linear regression tasks has been upvoted many times on Reddit and reshared dozens of times on various social media platforms. I hope Hacker Noon data scientists find it useful as well! 8. How Machine Learning is Transforming Biotech Machine learning is re-writing everything we thought we know about what's possible through biotech. 9. How Advanced Analytics Can Improve the Public Sector Advanced analytic models can identify and predict negative outcomes such as health and safety challenges or compliance risks that would be overlooked by manual. 10. IoT, Big Data and the Era of the Zettabyte Have you heard about the Internet of Things and Big Data? They are two very trending technologies that have evolved independently for a long time. 11. 5 Reasons to Invest in Analytics For Your Startup Now Data analytics are a startup's best friend, and here are five reasons why. 12. Data Impact in Public Health Accuracy: A Healthcare Expert's Quest to Educate the Public with Data The COVID-19 Pandemic has forced people to adapt to changing times and adopt new technologies. Using data to help track healthcare trends is part of this. 13. Ways To Overcome Linguistic Barriers with Language Technologies COVID-19 has impacted every other industry and has made people adopt newer norms. The traditional translation industry is no different. Several disruptions have been introduced to keep things moving, thanks to Big data and machine translation technologies that have enabled the world to do business as usual. 14. 8 Reasons Why Inventors Should Try This Free and Open-Source Patent Search Engine PQAI is a free and open-source patent search engine that uses artificial intelligence to search for patents using queries in natural language. 15. Investors Clamor for Digestible Data Analytics in the Fledgling Crypto Industry As DeFi data generation grows with the industry, there is an increased need for platforms that are able to digest and analyze this data for investors. 16. The Types and Benefits Of Cloud Computing In this article, we discuss the options available for businesses to make the correct choice in terms of cloud computing to complement a business' needs. 17. How AI Has Enhanced Sentiment Analysis Using Product Review Data Customer feedback is great. But have you been able to turn that feedback into meaningful customer insights? A few years back, brands depended on surveys to gauge customers’ feelings about how their products were performing. 18. 6 Biggest Limitations of Artificial Intelligence Technology While the release of GPT-3 marks a significant milestone in the development of AI, the path forward is still obscure. There are still certain limitations to the technology today. Here are six of the major limitations facing data scientists today. 19. Data Preparation: The Case for Using Automated, ML-Based Tools Data preparation has always been challenging, but over the past few years as companies increasingly indulge in big data technologies, data preparation has become a mammoth challenge threatening the success of big data, AI, IoT initiatives. 20. The Problems with Big Data and How AI Can Help, an Interview with Andrew Gryaznov, CTO at HyperC What is wrong with Big Data, how can classical AI solve these problems, and why is it possible now? 21. Indoor Positioning and Predicting the Most Suitable Boutiques in Shopping Malls for Customers Indoor navigation and machine learning combination both for helping users to find the most suitable stores and for helping stores to advertise their products. 22. How to Democratize Access to Data Insights for Businesses of All Sizes Messy government data has been part of the reason we've been unable to understand the COVID-19 pandemic. If federal organizations can't decode big data, what hope do small businesses have? 23. How To Use Change Data Capture for Fraud Detection Still relying on overnight processes to drive your decision making? Maybe it’s time to consider an evaluation of your CDC pattern that uses new technology. 24. Essential Guide to Scraping Google Shopping Results In this post, we will learn to scrape Google Shopping Results using Node JS with Unirest and Cheerio. 25. Eliminating Difference Between Business Intelligence analysts, Data Analysts or Data Scientists 🚀 There was a time when the data analyst on the team was the person driving digitalization in an adventurous data quest...and then the engineers took over. 26. Opinion: There’s Nothing Wrong With Being Tracked by Google Why you should be happy about companies collecting your data. 27. Big Data Analysis for the Clueless and the Curious Big data analytics has been a hot topic for quite some time now. But what exactly is it? Find out here. 28. What Are The Challenges of Monetizing and Selling Data? There have been great advancements in monetization opportunities in the last decade, but there are still challenges when it comes to generating big data analyti 29. The Failed Promises of Extract, Transform, and Load—and What Comes Next Faster, Better Insights: Why Networked Data Platforms Matter for Telecommunications Companies 30. Crunching Large Datasets Made Fast and Easy: the Polars Library Processing large data, e.g. for cleansing, aggregation or filtering is done blazingly fast with the Polars data frame library in python thanks to its design. 31. Kafka Authorization And NiFi Encryption to Amazon S3 Any typical ETL/ELT pipeline cannot be completed without having "kafka" keyword in the discussions. 32. Podcast - When Machine Learning Meets Privacy This is the first episode of a podcast series on Machine Learning and Data privacy. 33. SubQuery to Provide Indexing and Querying Infrastructure to Developers on Algorand SubQuery is a blockchain developer toolkit that makes it easier to build upcoming Web3 apps. 34. The eCommerce Turn of The Art Market: Trust, Transparency, And Trustworthiness Now that the online art marketplaces are finally going mainstream, how can the experience be matched to other online marketplaces? Data might be the key. 35. Data Product Managers and the Data Mesh With data becoming very ubiquitous in the enterprise, proper definition of a data product, its lifecycle and development process should be established. 36. Probabilistic Data Structures And Algorithms In Big Data Probabilistic data structures allow you to conquer the beast and give you an estimated view of some data characteristics 37. A Beginner's Introduction to Database Backup Security With more companies collecting customer data than ever, database backups are key. 38. Thrilled to be Recognized as Contributor of the Year - Data Science & Data Analytics Hooray! We have made it to the Hackernoon Awards. Xtract.io, the data provider's company is happy and elated to be part of #noonies2021. Join us in our victory! 39. Clean Up Your Data by Removing Duplicate Data Using these Tools In this blog, we will look at what a data deduplication software is, the most crucial features and functionalities found in such a tool, and how it can help you 40. A High Level Explanation of Data Types for Decision Makers There are three different types of data: structured data, semi structured data, and unstructured data. 41. 'At the Coalface of Implementing Data Stacks': kleene's Co-founder & CEO Andrew Thomas 2-minute look at the building of kleene.ai through a founder's eyes. 42. How to Use Public Keys in Data Lifecycles The data lifecycle (also known as the information lifecycle) refers to the full-time period during which data is present in the system. 43. Self-service Data Preparation Tools Can Optimize Big Data Efficiency for the IT Team Self-service data preparation tools are designed for business users to process data without relying on IT, but that doesn’t mean IT users can't benefit too. 44. The Best (and Worst) Punny Jokes Only Data Scientists Will Understand For the first KDnuggets post on Hacker Noon, we bring you a lighter fare of very nerdy computer humor from the series of self-referential jokes started on Twitter earlier this week. Here are some of our favorites. If you do understand all of the jokes, then you congratulate yourself on having excellent knowledge of Data Science and Machine Learning! If you have actually laughed at 2 or more jokes, then you have earned MS in Computer Humor! If you just smirked, you probably have a Ph.D. And I have a great joke about AGI, but it will be ready in 10 years. Enjoy, and if you have more, add them in comments below! Yann LeCun, @ylecun 45. Web Scraping con Python: Guía Paso a Paso La necesidad de extraer datos de sitios web está aumentando. Cuando realizamos proyectos relacionados con datos, como el monitoreo de precios, análisis de negocios o agregador de noticias, siempre tendremos que registrar los datos de los sitios web. Sin embargo, copiar y pegar datos línea por línea ha quedado desactualizado. En este artículo, le enseñaremos cómo convertirse en un "experto" en la extracción de datos de sitios web, que consiste en hacer web scraping con python. 46. 8 Ways to Gather and Leverage Customer Data of Your Ecommerce Website In this article, you will take a look at some of the different approaches you can use to gather and leverage customer data for your eCommerce website. 47. How to Improve Query Speed to Make the Most out of Your Data In this article, I will talk about how I improved overall data processing efficiency by optimizing the choice and usage of data warehouses. 48. How to Get Started with Data Governance Best Practices Long recognized as a must in the data-driven world, data governance has never been easy for big and tiny organizations alike. 49. How We Use dbt (Client) In Our Data Team Here is not really an article, but more some notes about how we use dbt in our team. 50. Processing Massive Amounts of On Demand Data Without Crashing NodeJS Main Thread Processing Massive Data On Demand Without Crashing NodeJS Main Thread 51. How to Back Up Exchange Online Data 52. Web Scraping con Python: Guía Paso a Paso La necesidad de extraer datos de sitios web está aumentando. Cuando realizamos proyectos relacionados con datos, como el monitoreo de precios, análisis de negocios o agregador de noticias, siempre tendremos que registrar los datos de los sitios web. Sin embargo, copiar y pegar datos línea por línea ha quedado desactualizado. En este artículo, le enseñaremos cómo convertirse en un "experto" en la extracción de datos de sitios web, que consiste en hacer web scraping con python. 53. 16 SQL Techniques Every Beginner Needs to Know This blog post explains the most intricate data warehouse SQL techniques in detail. 54. Top 5 Big Data Frameworks in 2021 These are the best Big Data Frameworks developers can learn in 2021. It includes Apache Hadoop, Apache Spark, Apache Flink, Apache Storm, and Apache Hive 55. How to Use Public Web Data for Talent Intelligence and Sourcing Learn how public web data can boost your talent sourcing efforts in both quality and quantity. 56. How Big Data Can Help Build Biotech Products New methods and discoveries, such as next-generation genome sequencing, generate vast amounts of data and transform the scientific landscape. 57. From Raw Data to Actionable Insights: The Power of Data Aggregation This article examines data aggregation processes: collecting data to present it in summary form. 58. Understanding the Main Differences between Structured and Unstructured Data In this, I explore structured, unstructured, and semi-structured data, as well as how to convert unstructured data, and AI’s impact on data management. 59. A Brief Intro to 8 Ways AI Could Improve Patient Care How much data does a hospital produce each day? How much information are they capable of storing, analyzing, and sharing with physicians and patients? 60. Big ‘Earth Observation’ Data: Challenges and Applications As nearly a thousand Earth observation satellites currently orbit the planet, terabytes of remote sensing data and satellite imagery of land, vegetation, water bodies, glaciers, urban landscapes, and other geographic features become available for end users across multiple industries. Modern GIS systems allow the collection of all such geospatial data in one place for a comprehensive analysis of the area under study. 61. Data Quality: Its Definitions And How to Improve It Utilizing quality data is essential for business operations. This article explores data quality definitions and how to maintain it for everyday use. 62. How AI Is Transforming The Future Of Healthcare Industry The power of Artificial Intelligence is echoing across many industries. But its impact on healthcare is truly life-changing. With its ability to mimic human cognitive functions, AI is bringing a paradigm shift in the healthcare industry. 63. The Importance of Hypothesis Testing Hypothesis tests are significant for evaluating answers to questions concerning samples of data. 64. An Intro to SQL for Data Scientists The importance of SQL and how to go about learning it 65. What Are the Key Differences Between Qualitative and Quantitative Data? This article uncovers the key differences between qualitative and quantitative data with examples. 66. Covid-19: Analysing The Spread Across Populations A large portion of mild and asymptomatic cases may go unreported. The data will never be perfect, the true cases are likely much larger as the testing frequency and effectiveness vary in different regions. 67. Scaling Off-Chain Data and Computation for Smart Contracts As storing information on the blockchain becomes more popular, the availability of smart contracts becomes more widespread. They behave according to established parameters, automatically letting events happen once specified conditions are met. 68. Being 'Chief Geek' and Running 15 Websites with Noonies Nominee Mathias Hellquist So who TF is Mathias Hellquist and what is a "Chief Geek"? Read this interview to find out. 69. Advantages and Disadvantages of Big Data Big data may seem like any other buzzword in business, but it’s important to understand how big data benefits a company and how it’s limited. 70. Build your Dataset from COCO with the Universal Data Tool If you haven’t heard of the Universal Data Tool yet, it’s an open-source web or desktop program to collaborate, build and edit text, image, video, and audio datasets with labels and annotations. 71. How Different Analyst Types Can Positively Impact Your Small Business Data analysis used to be considered a luxury of big business. 72. How to Migrate from Airflow to Dolphinscheduler in Two Steps Recently, Air2phin, a scheduling system migration tool, announced its open source. With Air2phin, users can migrate the scheduling system from Airflow to Apache 73. Top 8 Best Qlik Sense Extensions Qlik Sense is powerful data visualization and BI software. But sometimes its functions are not enough. Meet the best Qlik Sense extensions to do more with data! 74. Python vs JavaScript: Main Differences, Performance Comparison, and Areas of Application The complexity of modern web apps lies far beyond creating eye-catching user interfaces with countless elements. To enable lag-free experience and effortless scalability, it’s important to pay due attention to the architecture design, which can be pretty challenging. Under the hood of a full-featured online app, different frameworks and libraries can peacefully coexist with different programming languages used to build software. Since the equation may contain so many variables, it’s essential to master your knowledge of each potential system component to know when and why to use them. 75. Hadoop Across Multiple Data Centers Hadoop cluster across multiple data centers 76. Dealing With Replication, High-Performance Queries And Other Data Platforms Challenges Many products solve for global issues and load balancing but unless a platform is built from the ground up with the necessary backbones, it becomes a nightmare to manage. 77. "My manager gave me detailed instructions on what to do, but I kept asking why" #Noonies2021 Don't wait for an invitation to do product strategy, because you won't get it. 78. 7 Serious Security Issues in Big Data and How to Address Them Businesses will be able to reach their ultimate aim of leveraging data for better customer experience and retention if they use Big Data effectively. 79. The Benefits And Core Processes of Data Wrangling This article examines the process and methods of data wrangling: preparing data for further analysis by transforming, cleaning, and organizing it. 80. Public Health Improvements as a Result of Data Usage and Analysis in Healthcare Big data has made a slow transition from being a vague boogie man to being a force of profound and meaningful change. Though it’s far from reaching its full potential, data is already having an enormous impact onhealthcare outcomes across the world — both at the public and individual levels. 81. When Big Data Goes Bad: Rehabilitating Data Quality In a data-driven world, having data to make your decision provides a strong advantage... except when the data is bad. See how Datafold can help. 82. $DAG Will Do To Big Data What Bitcoin Did To Money Hello, Dear reader! 🧑💻 Here I talk about the Constellation Network, Inc. Why I think the Constellation is one of the most amazing companies! Why they will steal the show and create and set the standard for future Cybersecurity for Big Data. I give arguments to which I paid more attention than to others, as possible clearly and briefly. Go! 83. Busting AI Myths: "You Need Tons of Data for Machine Learning" Leading researchers like Karl Friston describe AI as "active inference" —creating computational statistical models that minimize prediction-error. The human brain operates much the same way, also learning from data. A common argument goes: 84. 5 Prominent Big Data Analytics Tools to Learn in 2020 Data, data and data. This seems to be what our world is swimming and immersing in. Why? The answer is simple: simply everything we use, such as mobile phones, and with it, all that it has, such as the social media, churn out unimaginable amounts of data. 85. The Advantages of a Hybrid Deployment Architecture See how a hybrid architecture marries the best of the SaaS world and on-prem world for modern data stack software. 86. How Big Data is Keeping Employees Engaged in the Age of WFH Big data is beginning to emerge as a key tool for businesses to successfully operate on a WFH basis. 87. Universal Data Tool Update: On-Premise Data Labeling If you haven’t heard of the Universal Data Tool yet, it’s an open-source web or desktop program to collaborate, build and edit text, image, video, and audio datasets with labels and annotations. 88. Use Amazon Personalize & Data in the Raw for Real-Time Recommendations: Start capturing website user data in 5 minutes or less with no developer resources or coding experience needed. 89. A Brief Introduction to Commit Logs Logs are everywhere in software development. Without them there’d be no relational databases, git version control, or most analytics platforms. 90. Top 5 Factors Behind Data Analytics Costs A custom integrated data analytics solution would cost at least $150,000-200,000 to build and implement. 91. Digital Technologies And Their Increased Role - What Does The Future Hold? Digital technologies offer more and more new opportunities. The advancement of technologies makes our life easier and our planet a better place to live. 92. Practical Tips to Improve Customer Experience with Data According to a report, almost 70% of companies compete on customer experience. 93. Machine Learning: Role in Pricing And Inventory Optimization If you want to make the right pricing and inventory decisions, then an AI-powered analytical solution is your best investment. Here’s why. 94. How GPUs are Beginning to Displace Clusters for Big Data & Data Science More recently on my data science journey I have been using a low grade consumer GPU (NVIDIA GeForce 1060) to accomplish things that were previously only realistically capable on a cluster - here is why I think this is the direction data science will go in the next 5 years. 95. Supporting 'Citizen IT': It’s Critical to Democratize Your Data Democratizing data to enable Citizen IT provides a competitive advantage to organizations - here's why. 96. SQL Databases Vs. NOSQL Databases The decision to choose a database for project is not that simple. But when it comes to choosing a database, the biggest decisions is picking a relational (SQL) or non-relational (NoSQL) data structure. 97. Diffusion by Push Technology Now Supports MQTT Support for the OASIS MQTT open standard protocol is the main feature added to Diffusion 6.6 Preview 2, the latest release of the Diffusion® Intelligent Event Data Platform. 98. Big Data's Influence on Decision Making in the Healthcare Industry Big data is transforming decision-making in healthcare and this article explores how it can be used to improve patient care, as well as its challenges. 99. Predictive Analytics and You: Stagnation by Design This story begins and ends with algorithms, those series of functions so mathy and boring that rather than think about them at all, most of us would prefer listening to our nine-year-old nephew rattle off a list of his 255 most-favorite Pokemon, organized from most to least interesting. 100. Big Brother Meets Black Mirror in the Middle Kingdom Imagine a world where everything you ever do or say is watched and rated by invisible eyes. 101. How to Improve VC Deal Sourcing Using Public Web Data Learn how public web data can help you improve your deal sourcing methods. 102. Is Data Monetization Dead? The advent of cryptocurrency and web3 has led to investigations and experiments into what ways could a total decentralized digital society manifest. 103. How to Achieve Optimal Business Results with Public Web Data Public web data unlocks many opportunities for businesses that can harness it. Here’s how to prepare for working with this type of data. 104. Automated Data Replication From AWS S3 To Microsoft Azure Storage Made Easy It may be a requirement of your business to move a good amount of data periodically from one public cloud to another. More specifically, you may face mandates requiring a multi-cloud solution. This article covers one approach to automate data replication from AWS S3 Bucket to Microsoft Azure Blob Storage container using Amazon S3 Inventory, Amazon S3 Batch Operations, Fargate, and AzCopy. 105. Introduction to Delight: Spark UI and Spark History Server Delight is an open-source an cross-platform monitoring dashboard for Apache Spark with memory & CPU metrics complementing the Spark UI and Spark History Server. 106. The Evolution of Big Data And Web Scraping As the CEO of a proxy service and data scraping solutions provider, I understand completely why global data breaches that appear on news headlines at times have given web scraping a terrible reputation and why so many people feel cynical about Big Data these days. 107. Is Your Business Ready for AI Implementation? Artificial intelligence (AI) and machine learning are no longer futuristic theories. They are now real technologies with real applications in numerous businesses. The Forbes Insights poll, together with Dell Technologies and Intel, showed that AI is a key component of digital development, but only a quarter of Chief Experience Officers surveyed say they have implemented these technologies in their company. What is the reason for such low AI penetration in organizations and is your company ready to use machine learning? In this article, we will share our thoughts on the impact of AI on business and how to implement it faster. 108. Can Your Organization's Data Ever Really Be Self-Service? Self-serve systems are a big priority for data leaders, but what exactly does it mean? And is it more trouble than it's worth? 109. Artificial Intelligence and Big Data Artificial Intelligence and Big Data. These two terms seem to permeate the tech world in every possible way one can think of. Along with giant terms like Machine Learning, IoT, blockchain and related ones, AI and Big Data are set to dominate our world in the years ahead. 110. Cloud Solutions Propelled Into The Spotlight Courtesy Of Covid-19 In the wake of the COVID-19 pandemic, cloud service solutions have been thrown into the limelight as companies and organisations across the globe grapple with the rapid shift to remote working and learning. With the widespread closure of non-essential organisations and businesses forcing organisations’ leaders to consider new and innovative approaches to shifting their businesses online, the move to cloud computing has become a far greater priority than ever before. The industry statistics demonstrate this: according to new figures from analyst firm Gartner, by the end of 2020 we will have seen the global public cloud services market reach $266.4 billion, up from $227.8 billion in 2019. 111. Apache Druid, TiDB, ClickHouse, or Apache Doris? A Comparison of OLAP Tools The OLAP experience of an automobile manufacturer. 112. A Dive into Education Tech Trends: Embracing Innovations to Get Smarter The latest trends that can redefine education, educational establishments and study approaches. 113. Web3.0 Powered Privacy: Decentralization for More Control and Transparency A look at the importance of data privacy in today's digital age, where personal information is being collected, used, and shared at an unprecedented rate. 114. 7 BFSI Trends in 2022: Big Data, Blockchain, and More BFSI sector is anticipated to witness major trend changes in the technology segment. The article will present details regarding the upcoming transformations. 115. 6 Database Migration Tools For Complete Data Integrity & More Database migrations are driven by benefits like lower costs, better features, and the ability to scale. However, the security of data is essential. 116. How To Drive Business Value through Smart Data Data is the most important asset in today’s world. It is rightly termed as the ‘crude oil’ or the ‘gold ore’ of modern times. The main crux lies in the fact that data though voluminous needs to be processed just-in-time for meaningful utilization and consumption. It is fundamental to time-based competition in the market, where businesses compete based on ‘who meaningfully engages the customer first’. 117. Emerging Food Technology Trends & Insights for 2022 The food industry is one industry that benefits from the use of technology, from data gathering, food quality, blockchain tech and supply chain tracking. 118. Data Playgrounds are The Cure for Slow and Inefficient DataOps Companies struggle with their DataOps due to a flawed, code-centric, and linear workflow. To succeed, they must build data playgrounds, not mere pipelines. 119. Is Web Scraping Stealing? Web scraping is a super helpful tool not just to make money but also to reveal injustices hidden in plain sight, or to call Russians to talk about the war 120. Accelerating Innovation: How Covid Has Prompted Technological Evolution Within Healthcare Let’s take a deeper look into some of the most significant tech innovations that have been prompted by the emergence of Covid-19. 121. AI, Big Data, Blockchain, and Edge: Welcome to 2020 Technological advancements and digitization have become inevitable in this online world. 122. How Different Industries Put Data Analytics to Use You must have heard about big data and the theory used behind it. However, are you aware of the top industries where data analytics is being used for changing the way we work in the actual world? Let's take a close look at the top big data industries and how they are getting reshaped by using data analytics. The main idea behind using big data is that it is a new method for gaining insight into the challenges faced by various companies each day. In earlier days it was not possible to collect and interpret a vast quantity of data because there was no technology available. 123. Protecting the Most Vulnerable Populations During COVID-19 Thousands of COVID-19 deaths have been linked to nursing home residents or their caregivers - but COVID-19 isn’t stopping there. Though hundreds of thousands have been infected, efforts taken by governments such as social distancing have been proven to work. Looking at and comparing cities of similar sizes who enacted social distancing guidelines at different times can give us some insight on how well social distancing works. 124. Extraer Datos del Website a Excel Automáticamente Para extraer datos de websites, puede usar las herramientas de extracción de datos como Octoparse. Estas herramientas pueden extraer datos de website automáticamente y guardarlos en muchos formatos, como Excel, JSON, CSV, HTML o en su propia base de datos a través de API. Solo toma unos minutos puede extraer miles de líneas de datos, la mejor es que no se necesita codificación en este proceso. 125. Why Big Data is Big Business: The Netflix Example Take a look at the following chart: 126. How to Setup Your Organisation's Data Team for Success Best practices for building a data team at a hypergrowth startup, from hiring your first data engineer to IPO. 127. Social Network Big Data Will Boost Website Traffic The importance of social media in business marketing cannot be overlooked. All you have to do is find the best ways to make the best use of it. One such important way to boost your website traffic easily through your social networks is by transport planning and using big data. 128. How Are Smart Cities Made 'Smart': Top 6 Enabling Technologies The ultimate goal of smart cities is to improve citizens’ quality of life, reduce the cost of living and attain a sustainable environment through technology. 129. Embedded data analytics and reporting tools that empowers Business analysts Embedded data analytics and reporting tools that empowers Business analysts 130. 4 Critical Steps To Build A Large Catalog Of Connectors Remarkably Well The art of building a large catalog of connectors is thinking in onion layers. 131. Leveraging AI for Insights-Driven Organizational Efficiency Gains With modern-day work largely centered on digital platforms, automating the handling of big data has become more important than ever. This is where Artificial Intelligence (AI) comes in— performing tasks more efficiently by imitating our abilities to learn and solve problems. As technology advances at breakneck speed, fueled by the IoT environment, it has paved the way for a synergistic relationship between Artificial Intelligence and Big Data. 132. Data Engineering Tools for Geospatial Data Location-based information makes the field of geospatial analytics so popular today. Collecting useful data requires some unique tools covered in this blog. 133. The Three Basic Benefits of a Virtual Data Room The popularity of online virtual data rooms has increased over the years. These are innovative software used for safe storage and sharing of files. As the world is modernizing, people are using advanced technology to carry out their daily tasks. As everything today is digital, it becomes more and more crucial to look for new methods to store files. Gone are the days when people used to pile up hard copies of all the files in the offices. Some people are still seen doing that which wastes half of their time. Imagine you have a business meeting in some time and you can’t find a specific file because there is a huge unorganized bundle of files in your office. With virtual data rooms, all your files are well organized. You do not have to get into a hassle of finding a certain file. With just one click, the file appears in front of you in no time. 134. 4 Ways in Which Predictive Analytics in Insurance is Paving the Way for the Future Predictive analytics in insurance is radically changing the way companies do business. It will soon be at the core of countless new technology solutions. 135. Product manager dead after ‘taking a step back’ off cliff 136. Crypto Use Explodes, Data Will Help Investors Make Better Decisions Investors need good data to make good decisions, and new AI platforms will provide deeper analysis 137. Building the Next-Generation Data Lakehouse: 10X Performance How to connect various data sources easily and ensure high query performance. 138. How Big Data Is Disrupting Big Business Right Now Image Credit: Unsplash 139. Startup Interview with Zoltan Csikos, Co-Founder & CEO, Neticle Neticle offers a range of text analytics tools for businesses. If you have textual data to analyze, Neticle has a solution for you! 140. How Big Data Will Impact the Accounting Industry If I say that we have officially entered into the age of data, it would not be farfetched. According to the World Economic Forum, the total data produced in a day would reach to 44 zettabytes in 2020. 141. Making Money Off Of Your Organization's Data - How It's Done From traditional sales to bounties to Digital Inversion, learn how to extract value from your data assets via Nevermined’s numerous commercialization models. 142. "'The Way We've Always Done Things' = Complacency," says Dan Voyce "Don't pay much attention to 'This is the way we have always done things' - it comes from a place of complacency and poor performance," is our favourite quote from this 2020 Noonies interview with Daniel Voyce (Australia), who’s been nominated for contributions to Hacker Noon's Big Data thought log. In this interview, Dan not only illuminates a big data professional perspective from down-under, but also concerns around the normalization of idiocy as well as some serious excitement around GPU Datascience. Read on! 143. 5 Ways to Become a Leader That Data Engineers Will Love How to become a better data leader that the data engineers love? 144. How to Think Like a Data Scientist or Data Analyst Data science is a new and maturing field, with a variety of job functions emerging, from data engineering and data analysis to machine and deep learning. A data scientist must combine scientific, creative and investigative thinking to extract meaning from a range of datasets, and to address the underlying challenge faced by the client. 145. How to Analyze and Process Unstructured Data in 5 Simple Steps In this article, we’ll look at how to analyze and process unstructured data while using business intelligence tools to simplify the entire process. 146. Data Will Never Be Clean But You Can Make it Useful Understanding how to clean data is essential to ensure your data tells an accurate story 147. 4 Data Transformations Made Spreadsheet-Easy Gigasheet combines the ease of a spreadsheet, the power of a database, and the scale of the cloud. 148. 3 Best Hadoop Alternatives to Consider for Migration In this article, we will discuss why Hadoop is losing popularity and what other options are available that could potentially replace it. 149. Top 10 Best Web Scraper And Data Scraping Tools Data extraction has many forms and can be complicated. From Preventing your IP from getting banned to bypassing the captchas, to parsing the source correctly, headerless chrome for javascript rendering, data cleaning, and then generating the data in a usable format, there is a lot of effort that goes in. I have been scraping data from the web for over 8 years. We used web scraping for tracking the prices of other hotel booking vendors. So, when our competitor lowers his prices we get a notification to lower our prices to from our cron web scrapers. 150. How to Create Bullseye Charts with JS: COVID-19 Vaccine Pipeline Bullseye charts are widely used in drug pipeline & clinical trials data analysis. Learn how to create one in JavaScript and explore the COVID vaccines by phase. 151. A Day in the Life of a Data Scientist at a Climate Change Startup A guided tour into the life of a data scientist at a climate-tech startup. 152. How to Tell the Difference Between Data Warehouses, Data Lakes and Data Lakehouses Struggling to harness data sprawl, CIOs across industries are facing tough challenges. 153. How the Future of Automation Will Drive Innovation Automation is an exciting prospect. Who doesn’t like the idea of having menial tasks completed quicker and more effectively than they could have been by a human? 154. How Big Data Can Bring Transformative Improvements to Medical Care In the healthcare landscape, providers and lawmakers alike are faced with the challenge of making the best possible decisions for patients and the industry as a whole. From choosing the best treatments to using resources in a responsible manner, medical leaders are making decisions on a daily basis that can significantly impact health outcomes and costs. 155. Understand Data Analytics Framework Using An Example From General Electric Company The framework will allow you to focus on the business outcomes first and the actions and decisions that enable the outcomes. 156. Retraining Machine Learning Model Approaches Retraining Machine Learning Model, Model Drift, Different ways to identify model drift, Performance Degradation 157. Data Organization – The Great Differentiator in the Digital Era In business, efficient processes can make or break an organization. If processes are not executed properly, companies lose time, money, and damage their reputation. 158. Why Self-Service Analytics Tools Are Important For Business Decisions Making How to use Big Data, Self-Service Analytics Tools and Artificial Intelligence to Empower your Company Business Decisions Makers with State Of The Art Software 159. How IoT Data Can Help Accelerate Digital Transformation Every business is dreaming about how digital transformation will push productivity and profits to the max. The buzzword (or rather the phrase) of the last couple of years is known for “driving efficiencies and innovation”. 160. What Is A Data Mesh — And Is It Right For Me? Ask anyone in the data industry what’s hot and chances are “data mesh” will rise to the top of the list. But what is a data mesh and is it right for you? 161. Eco-Big Data Applications in the City: Cleaning Up with IoT and ML Digitalization is possible not only in enterprises. Digital transformation is catching up even with cities to make them more convenient for residents and less harmful to the planet. How to quickly monitor garbage cans, the state of forest parks, cycling and air purity with the help of big data, machine learning and the Internet of things? 162. Why AI Unified Analytics is Good for Your Business AI unified analytics can help businesses collect and analyze the data that AI tools require. Learn more about how AI unified analytics is good for business! 163. Pilosa: A Scalable High Performance Bitmap Database Index Big data is a big problem, at least getting anything useful out of it. Every day there is about three quintillion (the next step up is sextillion or one zettabyte) bytes of data created and only about 20% of it is structured and available to easily process. Nearly all useful processing that is done relies on a philosophy that is little changed from the green bar reports we were generating during the night shift and handing out up till the turn of the century. The whole map/reduce process is overnight batch processing, you aren’t working on live data, you are working on a snapshot, which might be fine for some companies, but for others, they need to be able to make decisions on high-velocity inbound data in near/real time. 164. Why Data is Pivotal to Email Marketing Email marketing today thrives on personalization. With Data, you have all it takes to “hit the bull’s eye". 165. How Programming, AI, and Big Data is Giving Google A Chance to Save the World Big business and saving the planet often do not go hand in hand, however in some cases they do. Take a look at how Google plans on saving the future with tech. 166. Public Web Data for Business: Common Challenges And How to Solve Them Businesses working with public web data experience various challenges. This article covers the most common ones and how to overcome them. 167. Using Data and Social Graphs for Clinical Trials Building a social graph — knowledge graph — to improve clinical trials' processes and reduce costs by providing better clarity and access to heterogeneous datasets. 168. Digging into Postgres's Lesser Known Features Postgres Handles More than You Think 169. Scale Your Data Pipelines with Airflow and Kubernetes It doesn’t matter if you are running background tasks, preprocessing jobs or ML pipelines. Writing tasks is the easy part. The hard part is the orchestration— Managing dependencies among tasks, scheduling workflows and monitor their execution is tedious. 170. Digging Into Amazon's Privacy Policy Amazon has developed a reputation for delivering some of the lowest prices for all types of products, and one of the best delivery systems in the world. Part of what makes this possible is Amazon’s extensive use of people’s data. We’re taking a look at which information Amazon collects and how it collects that information. 171. From Big Data to Personal Lives: This Is How AI-Powered Tools Will Help Today’s Professionals “AI is everywhere around us. We are living with it every day, and we are loving it.” 172. Best Types of Data Visualization Learning about best data visualisation tools may be the first step in utilising data analytics to your advantage and the benefit of your company 173. Data Lineage is Like Untangling a Ball of Yarn Data lineage is a technology that retraces the relationships between data assets. 'Data lineage is like a family tree but for data' 174. Buckle Up and Enjoy Some Graph Therapy Graph Therapy. The Year of the Graph Newsletter, June / May 2020 175. The Glorious Return of the Conference: Highlights from My First Tech Conference in 2 Years As the world reopens, it's becoming evident that the new Insuretechs don’t see what they are doing as disruption but as an evolution of their strategies. 176. Big Data: 70 Increíbles Fuentes de Datos Gratuitas que Debes Conocer para 2020 Por favor clic el artículo original：http://www.octoparse.es/blog/70-fuentes-de-datos-gratuitas-en-2020 177. Building a Large-Scale Interactive SQL Query Engine with Open Source Software This is a collaboration between Baolong Mao's team at JD.com and my team at Alluxio. The original article was published on Alluxio's blog. This article describes how JD built an interactive OLAP platform combining two open-source technologies: Presto and Alluxio. 178. Hadoop for Hoops: Explore the Whole Ecosystem and to Know How It Really Works Technological evolution has changed the landscape, everything which we feel and hear today is revolving around some of the modern technology. This technology involves Artificial Intelligence, big data, cloud computing, data science, and much more, which has changed the landscape to a great extent. To integrate this technology, many of the IT professionals are finding and implementing the trajectory of today's modern technologies. 179. Hacking Your Way to Being an All-Star [Infographic] What does it take to make a team leader who pulls a team together? How do these qualities lead a player to become a strong contender for the NBA All-Stars team? Great basketball players know their teammates’ strengths and weaknesses and they understand how to play to every player’s strengths to make the team stronger as a whole. By setting a good example and remaining optimistic about the team as a whole, Tobias Harris has proven his value as a team player to the 76ers. 180. Data Science Training and Data Science - Machine Learning With Python The requirement for its stockpiling also grew as the world entered the period of huge information. The principle focal point of endeavors was on structure framework and answers for store information. When frameworks like Hadoop tackled the issue of capacity, preparing of this information turned into a challenge. Data science began assuming a crucial job to take care of this issue. Information Science is the fate of Artificial Intelligence as It can increase the value of your business. 181. Industry 4.0’s Ultimate Impact on Manufacturing Business The Fourth Industrial Revolution, more popularly coined as Industry 4.0, is brought upon us by restlessly growing volumes of data and all-consuming automation. These are the major modern IT tendencies that cover absolutely any type of business. The ultimate impact of Industry 4.0 is especially focused on the manufacturing sector. 182. Bits and Bytes and Data Delights Limarc Ambalina, Ellen Stevens, and Amy Tom chat about data privacy ☠️ Humans are in loooove with the internet, and data production is becoming more rampant and 183. Web Scraping API para Extracción de Datos: Una Guía para Principiantes ¿Alguna vez te sucede cuando la gente te pide que escribas una API separada para integrar datos de redes sociales y guardar los datos sin procesar en tu base de datos de análisis en el sitio? Definitivamente quieres saber qué es la API, cómo se usa en web scraping y qué puede lograr con ella. Echemos un vistazo. 184. Low-Code Development Helps Data Scientists Uncover Analytical Insights Emerging low-code development platforms enable Data Science teams to derive analytical insights from Big Data quickly. 185. Interpretation of Visualizations of Soil Data and Weather APIs Learn how to visualize and interpret weather APIs and soil data in different graphs using python libraries, and Google Collab. 186. Using Upsolver To Get Insights Into Your Company's Big Data Upsolver is a no-code data lake engineering platform for agile cloud analytics. Let's see how easy it is to use. 187. AI: From ZERO to H...aving A Lot of Questions (Part I) People are just like a Swiss Army Knife, but we are born with no tools on it. Everything we learn might become a new tool. With enough tools, we can accomplish everything. With the right tools, we can accomplish it faster, better and enjoy the endorphin rush. 188. Analyzing Data From U.S. Road Accidents With Data Visualization In this article, we would be analyzing data related to US road accidents, which can be utilized to study accident-prone locations and influential factors. 189. How to Use Business Intelligence: 66% of Companies Want to Be More Data-Driven in 2021 How do BI solutions help to make the decision-making process driven by data, improve CX, and speed up reporting? And how can you implement it yourself? 190. How Will Blockchain Fix the Centralization of Data? “In order to have a standard of value [cryptocurrency] must stand outside all value schemes. It must have value in and of itself." 191. "Using this method, I went from a teller to an executive," says Carlo Martinez CEO of Steppingblocks How I became obsessed with helping students connect college degrees to careers sooner. So, I decided to build a platform and call it Steppingblocks. 192. What is RFM (Recency, Frequency, Monetary) Analysis? RFM analysis is a data-driven customer segmentation technique that allows marketing professionals to take tactical decisions based on severe data refining 193. 9 Best Data Integration Software in 2022 Every business needs to collect, manage, integrate, and analyze data collected from various sources. Data integration software can help! 194. Build vs Buy: What We Learned by Implementing a Data Catalog Why we chose to finally buy a unified data workspace (Atlan), after spending 1.5 years building our own internal solution with Amundsen and Atlas 195. Performance Benchmark: Apache Spark on DataProc Vs. Google BigQuery When it comes to Big Data infrastructure on Google Cloud Platform , the most popular choices Data architects need to consider today are Google BigQuery – A serverless, highly scalable and cost-effective cloud data warehouse, Apache Beam based Cloud Dataflow and Dataproc – a fully managed cloud service for running Apache Spark and Apache Hadoop clusters in a simpler, more cost-efficient way. 196. How to Use Node Streams to Transform the Largest POI Database OpenStreetMap (OSM) is maybe the most extensive open data project for geo-data. It has rich information on points of interest (POIs), such as apartments, shops, or offices, globally. 197. Scrape Google Scholar Results With NodeJS, Unirest and Cheerio This article will teach us to scrape Google Scholar Result pages with Node JS using Unirest and Cheerio. 198. How Big Data Can Help to Analyze Social Media Performance During the last decade, social networking sites/apps have become the most important channels of communication. 199. Data Location Awareness: The Benefits of Implementing Tiered Locality Tiered Locality is a feature led by my colleague Andrew Audibert at Alluxio. This article dives into the details of how tiered locality helps provide optimized performance and lower costs. The original article was published on Alluxio’s engineering blog 200. Artificial Intelligence: Multimillennial Data Transmitted To Machines With Brains We are gradually encoding human knowledge in seas of annotated data 201. Best Practices For Apache Kafka Configuration Having worked with Kafka for more than two years now, there are two configs whose interaction I've seen be ubiquitously confused. 202. Semi-Supervised Machine Learning Algorithms Artificial intelligence is a system that can not only solve assigned tasks but also learn how to solve new problems, including creative ones. Previously, this process was available only to the human brain, but now artificially created programs can also do this. The AI system needs learning algorithms to study and create corresponding patterns that can improve the program and provide better results in the future. 203. How this Web3 Project is Unlocking a Trillion-Dollar Data Economy with Data NFTs Learn why data could become the most promising NFT utility that sets the foundation for a valuable trend: Data Finance (DataFi). 204. AWS Snow Family: An Old Solution to a New Problem The AWS Snow Family is a group of three products that solved the problem of slow data transfers and edge computing associated with cloud storage. 205. Top 3 Benefits of Insurance Data Analytics The Importance of data analytics and data-driven decisions across the board and in this case insurance data. 206. 6 Biggest Differences Between Airbyte And Singer We’ve been asked if Airbyte was being built on top of Singer. Even though we loved the initial mission they had, that won’t be the case. Aibyte's data protocol will be compatible with Singer’s, so that you can easily integrate and use Singer’s taps, but our protocol will differ in many ways from theirs. 207. Lessons for Improving Training Performance — Part 1 Part 1: Lower precision & larger batch size are standard now 208. The Gartner Hype Cycle Report and the Future of Data Gartner identifies data labeling as one of the key factors responsible for the ongoing evolution of AI technology and rapid AI-powered product development. 209. 3 Easy Ways to Improve The Performance Of Your Python Code I. Benchmark, benchmark, benchmark 210. A Deep Dive Into Facebook’s AI Transcoder Just over a week, most of you would have heard that Facebooks AI research team (FAIR) developed a neural transcompiler, that converts code from high level programming language like C++, Python, Java, Cobol into another language using ‘unsupervised translation’ . The traditional approach had been to tokenize the source language and convert it into an Abstract Syntax Tree (AST) which the transcompiler would use to translate to the target language of choice, based on handwritten rules that define the translations, such that abstract or the context is not lost. 211. Holy Land of Crypto Users: How does Web3.0 Data Empower Centralized Exchanges? Designing a data-oriented, user-incentive mechanism is a good path when developing the future of centralised exchanges for the cryptocurrency industry. 212. Containerization of Spark Python Using Kubernetes Introduction 213. Top 10 On-Demand IT Certifications With Highest Pay: 2020 Edition Information Technology (IT) certification can enrich your IT career and pave the way for a profitable way. As the demand for IT professionals increases, let's look at 10 high-paying certifications. The technology landscape is constantly changing and the demand for information technology certification is also getting higher. Popular areas of IT include networking, cloud computing, project management, and security. Eighty percent of IT professionals say certification is useful for careers and the challenge is to identify areas of interest. Let's take a look at the certifications that are most needed and the salaries that correspond to them. 214. Data Privacy is Becoming More Important for Users in 2022 A look at how data privacy is becoming more important for users in 2022 215. BitsCrunch Raises $3.6 Million from Coinbase Ventures, Crypto.com Capital and Animoca Brands BitCrunch has raised $3.6 million in a private round of funding led by Animoca Brands, including Coinbase Ventures, Crypto.com Capital and Polygon Studios. 216. How to Build a Data Stack from Scratch Overview of the modern data stack after interview 200+ data leaders. Decision Matrix for Benchmark (DW, ETL, Governance, Visualisation, Documentation, etc) 217. Data Journalism 101: 'Stories are Just Data with a Soul' Gone are the days when journalists simply had to find and report news. 218. Providing Next Generation Customer Experience with Sagi Eliyahu, CEO at KMS Lighthouse This article talks about how artificial intelligence and machine learning tools are used to improve and automate customer experience with automated smart reply. 219. Uploading a 1 Million Row CSV File to the Backend in 10 Seconds Uploading 1 million row size large CSV to mongoDB using nodejs stream 220. Don't Let Them Fool You: Manipulative Strategies Used By Big Tech Companies To Sell You Stuff Do you know how your apps work? Are you aware of what tech companies are doing in the back with your data? And what’s more revealing: do you know which of your action are actually influenced by those apps? When you take a trip with Uber, buy stuff on Amazon, or watch a movie on Netflix: when are you consciously deciding and when are you being heavily influenced? 221. An In-depth Guide on Web Scraping Web scraping - A Complete Guide: In this blog, we will learn everything about web scraping, its methods and uses, the correct way of doing it. 222. Automate Submissions for the Numerai Tournament Using Azure Functions and Python Python Automation with Azure Functions, to compete in the weekly Numerai tournament. 223. Can Big Data Solutions Be More Accessible And Affordable? Below you can find the article of my colleague and Big Data expert Boris Trofimov. 224. How to Improve Data Quality in 2022 Poor quality data could bring everything you built down. Ensuring data quality is a challenging but necessary task. 100% may be too ambitious, but here's what y 225. Graph Databases: Full Detailed Review There are many ideas and considerations behind graph databases. This includes their use cases, advantages, and the trends behind this database model. There are also several real-world examples to dissect. 226. The Top Big Data Consulting Firms Thanks to big data, today an organization can quickly obtain the necessary information from an unordered data set and deploy it effectively. The growing popularity of big data analytics has led to a significant increase in the number of companies providing big data solutions and related services. 227. The Essential Architectures For Every Data Scientist and Big Data Engineer Comprehensive List of Feature Store Architectures for Data Scientists and Big Data Professionals 228. Enterprise Blockchain for SmartCities What is SmartCity? 229. Interpreting Big Data: Data Science vs Data Analytics Data Science and Data Analytics are quite diverse but are related to the processing of Big data. The difference lies in the way they manipulate data. 230. How Much Can You Make as a Data Scientist? Wondering how much data scientists make? We're here to help you find out about salaries in Data Science and how they are influenced by various factors. 231. Native Analytics On Elasticsearch With Knowi Table of Contents 232. How To Query JSON in Couchbase via Collections and Scopes This week I’m attending the 3-day Couchbase Connect event and will be reporting on some of the topics that I find most interesting. 233. Analyzing Montreal’s BIXI Ridership With Data And Visuals Been to Montreal? Have you heard of the term bixi? Well, this article will educate you about bixi ridership and the factors that affect it. 234. SQL Queries: Why You Need SQL-Agnostic Parsing No need to be an expert in thousands of combinations of SQL, data types, and databases to master SQL queries. A good SQL agnostic parser will take care of all. 235. Data Is Now a Luxury Good: Here’s Why (It Shouldn’t Be) When was the last time you read a privacy policy? 236. Open Source is the Only Way to Address the Long Tail of Integrations Wouldn’t it be great to bring the time needed to build a new data integration connector down to 10 minutes? This would definitely help address the long tail of 237. What Is Big Data? Understanding The Business Use of Big Data Analytics Big data analytics can be applied for all and any business to boost their revenue and conversions and identify their common mistakes. 238. Allstate's Car Insurance Algorithm: How Insurance Algorithm Squeezes Big Spenders Seven years ago, Allstate Corporation told Maryland regulators it was time to update its auto insurance rates. The insurer said its new, sophisticated risk analysis showed it was charging nearly all of its 93,000 Maryland customers outdated premiums. Some of the old rates were off by miles. One 36-year-old man from Prince George’s County, Md., who Allstate said in public records should have been paying $3,750 every six months, was instead being charged twice that, more than $7,500. Other customers were paying hundreds or thousands of dollars less than they should have been, based on Allstate’s new calculation of the risk that they would file a claim. 239. How Big Data Can Help Personalize Your Ecommerce Store Data is everywhere. Every single detail you have ever provided online – from your address to the advertisements you’ve clicked on –is stored by browsers and applications. 240. The Importance of Monitoring Big Data Analytics Pipelines In this article, we first explain the requirements for monitoring your big data analytics pipeline and then we go into the key aspects that you need to consider to build a system that provides holistic observability. 241. How to Gather Actionable Customer Data With Social Media Before you can start finding things out about your audience, you have to figure out what you want from your social media marketing strategy. 242. The Hitchhiker's Guide to pySpark DataFrames Big Data has become synonymous with data engineering. But the line between Data Engineering and Data scientists is blurring day by day. At this point in time, I think that Big Data must be in the repertoire of all data scientists. 243. How Big Data is Shaping Adaptive Learning Big data analytics will likely drive more widespread adoption of adaptive learning tools, especially regarding big data for education and learning environments. 244. What Apple And Spotify Know About Me Unsurprisingly, the data that our apps have collected about us is both impressive and concerning, though it can be very interesting to review and explore it. 245. A Brief Introduction to 5 Predictive Models in Data Science Predictive Modeling in Data Science is more like the answer to the question “What is going to happen in the future, based on known past behaviors?” 246. Why We Should Have Different Databases Today there are hundreds of SQL and NoSQL databases. Some of them are popular, some are ignored. Some are user-friendly and well documented and some are hard to use. Some are open sourced and some are proprietary. And, perhaps, the most important - some are scalable, optimized, highly available and some are difficult to scale or maintain. 247. Effective Use of Big Data and Analytics for Business Ventures Business data analytics is often a very complex and intensive process to execute. In the era of big data analytics where a large set of varied data needs to be analyzed in order to uncover insightful information, things become more complex. However, such a comprehensive data analysis model will help uncover various hidden patterns, market shifts, and trends, unknown correlations, customer behavior, etc. Getting an actionable insight into these will help the organizational decision-makers to make well-informed decisions. 248. Distributed Storage is the Best Data Storage Tool for The Metaverse The most suitable data storage tool for Metaverse is undoubtedly distributed storage. 249. Top 7 Trends of Digital Transformation in Higher Education Higher Education is highly influenced by today's digital transformation and technological advances. The student learning experience can be boosted with the use 250. How to Migrate Data from an MSSQL Server to PostGreSQL? Thinking of shifting to a new database management engine? Here's how to migrate data from SQL server to PostgreSQL. 251. Don't Be Data-Driven. Become Purpose-Driven and Data-Assisted. 252. Top Industry Trends for AI Marketing Companies that embrace AI will be able to test, learn, and iterate much faster, raising the competitive bar for learning. 253. Web Scraping Google Maps Reviews In this post, we will learn to scrape Google Maps Reviews using the Google Maps hidden API. 254. Using Rate Limiting Algorithms for Data Processing Pipelines You may have already heard of rate limiting associated with REST API consumption. In this article I’ll show you a more complex use of this component... 255. Can Blockchain Technology Help with Our Growing Privacy Problems? Since the Internet's introduction to the public from the academic world, privacy issues have existed. Blockchain technology may be able to change this. 256. The People and Tech Behind Data Science What is a data scientist? The job has been around for hundreds of years, though as you may suspect things have changed significantly, especially over the last century. In the 1740s Bayes’ Theorem posited that when new data was added to an existing belief, the result was a new and improved belief. This is the basis for the scientific method, by which scientists discover better and better explanations for things. When applied to data, the scientific method creates data science, in which data scientists can use the piles of data people are generating to discover new and better predictions about the future. 257. How Big Data and Artificial Intelligence Will Go Hand in Hand? The emergence of technology is playing an inevitable role in business. It’s drastically transforming the way people work together in an organization. Both these technologies are revolutionizing every aspect of our life. These technologies are creating a culture where the collaboration of IT leaders and businesses results in realizing values from all generated data. 258. Predictive Analytics for Maintenance Events The predictive analytics machine learning model worked well to provide alerts before the engine values went beyond thresholds avoiding expensive repair cost. 259. The Ways in Which Big Data can Transform Talent Management and Human Resources Big Data is changing human resource management for good. We explore 4 major ways data analytics is upending & expanding the role of human resource departments. 260. Legal Billing Software for Busy Lawyers, an Overview Lawyers, accountants and auditors who are typically paid by the hour, have a hard time getting paid what they are truly owed. Legal billing software may just help. 261. Debunking The Top Myths Surrounding AI Myths about artificial intelligence range from fearful reports of robots to outlandish expectations of the technology. Today, consumers encounter artificial intelligence continuously through smartphones, customer service centers, websites, and appliances. Surveys show that nearly nine in 10 Americans use some form of artificial intelligence device, and 79% of people report AI having a perceived positive impact on their lives. Despite the overwhelmingly positive uptake of the technology, films, art, and literature have long warned about the potential dangers of AI in science fiction storytelling. So, how much of this is based on reality? 262. A Guide on The Future of ETL: EL(T) not ELT How we store and manage data has completely changed over the last decade. We moved from an ETL world to an ELT world, with companies like Fivetran pushing the trend. However, we don’t think it is going to stop there; ELT is a transition in our mind towards EL(T) (with EL decoupled from T). And to understand this, we need to discern the underlying reasons for this trend, as they might show what’s in store for the future. 263. How to Analyze and Visualize the Game of Thrones Character Relationships The hit series Game of Thrones by HBO is popular all over the world. Besides the unexpected plot twists and turns, the series is also known for its complex and highly intertwined character relationships. In this post, we will access the open source graph database Nebula Graph with NetworkX and visualize the complex character connections in Game of Thrones with Gephi. 264. Paying Crypto Taxes: Nuisance or Cost of Doing Business? TRASTRA founder and CEO Roman Potemkin on what is right, wrong, and unclear with implementing crypto taxes. 265. 4 Ways Data Science Helps Streamline Business Operations Data Science has changed the way organizations collect, analyze, and process different types of information. 266. A Quick Guide To Business Data Analytics For many businesses the lack of data isn’t an issue. Actually, it’s the contrary, there’s usually too much data accessible to make an obvious decision. With that much data to sort, you need additional information from your data. 267. ACID Transactions: Fundamentals of Delta Lake - Part 1 Delta Lake is an open-source storage layer that brings ACID transactions to Apache Spark™ and big data workloads. 268. Behavioral Intent Prediction Is Coming. Are We Ready? It can feel at times like we live in a science fiction future. We hold the whole of human knowledge in palm-sized devices that are constantly connected to the Internet. We speak to our computers and they respond with seemingly intelligent feedback. 269. Data Science Teams are Doing it Wrong: Putting Technology Ahead of People Data Science and ML have become competitive differentiator for organizations across industries. But a large number of ML models fail to go into production. Why? 270. Turn Big Data into a Big Success: 5 Tips for Effective Big Data Analytics Organizations must acquire appropriate measures for turning their big data into a big success. 271. The Essential Data Cleansing Checklist After some time working as a data scientist in my startup, I came to a point where I needed to ask for external help with your project. 272. Data Analytics is a Journey It is 2020 and the data analytics has gained so much attention even outside of the tech community. "Data is gold", they say - no one wants to be left behind. However, getting the right strategy is neither a straightforward nor static process. 273. How to Start with Web Scraping and Why You Don't Need to Code Collecting data from the web can be the core of data science. In this article, we'll see how to start with scraping with or without having to write code. 274. 5 Simple Ways to Kickstart Your Freelance Data Science Career If you’ve been itching to get your feet wet in the field, these steps will provide you with lots of valuable ideas and suggestions to kickstart your career. 275. Building AI Products with Big Data Credits: Thanks to our sponsor Amazon, the Advancing Women in Product Team: Keshav Attrey, Reeba Monachan Attrey, Kanika Kapoor, Alok Gupta, Jackie Yen, our AWIP volunteers and our panelists. 276. What Personal Details Are You Sharing Without Knowing? Unless you have changed your web browser default settings it is quite likely you are leaking personal details as you move around online. But just how much? 277. Facebook: The Magic 8 Ball It is easier for a camel to pass through the eye of a needle than for a homo sapien to quit this junk. 278. Introduction To Amazon SageMaker Amazon AI/ML Stack 279. How Big Data and AI Help People Make Smarter Investments Big data, artificial intelligence, and machine learning are some of the hottest technologies out there. Well, machine learning has existed since the late 1950s, and big data got first coined in 2005. However, it is only in the last decade, or so that computer engineers, scientists, and corporations have tried widespread implementations of these technologies. 280. 5 Essential Product Classification Papers for Data Scientists Product categorization/product classification is the organization of products into their respective departments or categories. As well, a large part of the process is the design of the product taxonomy as a whole. 281. Could Blockchain and Big Data Come Together To Open Up A New Chapter in Data Integrity? Whenever the term “Blockchain” comes across, many relate it with cryptocurrencies like Bitcoin. Yes, this technology has truly transformed the world of virtual currencies by speeding up transactions, providing privacy and transparency, and many more. 282. Java or Python: Which One Should a Data Scientist Learn? Data science is one of the most promising fields in tech. To succeed in the field, mastery over programming languages like Java and Python is essential. 283. Certify Your Data Assets to Avoid Treating Your Data Engineers Like Catalogs Data trust starts and ends with communication. Here’s how best-in-class data teams are certifying tables as approved for use across their organization. 284. Online Privacy is Not an Option: It's a Necessity How the challenge of protecting personal information online led to data protection and privacy laws in the EU and U.S. 285. What Happened to Hadoop? What Should You Do Now? by Monte Zweben & Syed Mahmood of Splice Machine 286. Future of Marketing: How Data Science Predicts Consumer Behavior Gradually, as the post-pandemic phase arrived, one thing that helped marketers predict their consumer behavior was Data Science. 287. Building Sustainable AI/ML Solutions in the Cloud with Federated Learning Compared to centralized training and cooling mechanisms adopted at data centers, how can Federated Learning help us combat detrimental environmental impacts? 288. High-Utility DeFi Data Analytics Tools For Crypto Investors These four growing platforms will give investors the tools they need to make smarter decisions 289. Kannada-MNIST:A new handwritten digits dataset in ML town TLDR: 290. As AI Gets More Emotionally Intelligent, So Must We How people behave in solitude is vastly different than how they behave in public, but the foundation of one’s persona remains constant. Dancing around the apartment when nobody’s watching expresses a secret desire to do so on a grand stage, but humans modulate those whims as societal norms dictate. 291. Blockchain Protects From Data Miners But Is Also A Perfect Tool For Data Mining The article tells what happens when blockchain meets online advertising. 292. 6 Places to Start a Career in Data Science in 2022 How to become a data scientist? Want to become a Data Scientist? Here are the resources. Resources to Become a Data Scientist 293. Data Lakes Are Crucial to Business Analytics and Big Data Processing Big data is a sort of Data addition that contains greater variety, arriving in increasing volumes and with more velocity which is also called three Vs. It could explain in several words by severals but actually what stands for it. 294. Not Only Python: Problems, Errors and Alternatives In this article, we will explore the emergence of new machine learning languages, how they have eroded Python's market share. 295. Big Data Analysis on Blockchain with CEO of Covalent, Ganesh Swami I sat down with Ganesh Swami, co-founder and CEO at Covalent, a Blockchain Big Data analytics firm, to discuss the Ethereum ecosystem. 296. How AI Is Transforming Your Smartphone The tech industry and the world are relying on artificial intelligence to solve big problems such as cybersecurity, healthcare and sustainability. 297. Machine Learning for Fraud Prevention Machine Learning aids e-commerce to foil attempts at payment fraud, as they happen. 298. Machine Learning Concepts In Python For your Next App Python can be used in machine learning, especially through using these basic machine learning concepts as building blocks for data analysis and other functions. 299. Powering the Future: Decentralized Oracles and Metaverse DNA In the decade-long history of blockchain and distributed ledger technology (DLT), rapid developments have led to consistent advances in the capabilities of decentralized financial platforms. By today’s standards Bitcoin has its limits: it supports value transfer and the storage of metadata within those transfers, but little else. With a block time of 10 minutes and a maximum block size of roughly four megabytes, it is also extremely slow compared to the emergent blockchains of the past few years. 300. Docker Dev Workflow for Apache Spark The benefits that come with using Docker containers are well known: they provide consistent and isolated environments so that applications can be deployed anywhere - locally, in dev / testing / prod environments, across all cloud providers, and on-premise - in a repeatable way. 301. How Synthetic Data is Accelerating Computer Vision In the spring of 1993, a Harvard statistics professor named Donald Rubin sat down to write a paper. Rubin’s paper would go on to change the way that artificial intelligence is researched and practiced, but its stated goal was more modest: analyze data from the 1990 U.S. census, while preserving the anonymity of its respondents. 302. Common RAID Failure Scenarios And How to Deal with Them Most businesses these days use RAID systems to gain improved performance and security. Redundant Array of Independent Disks (RAID) systems are a configuration of multiple disk drives that can improve storage and computing capabilities. This system comprises multiple hard disks that are connected to a single logical unit to provide more functions. As one single operating system, RAID architecture (RAID level 0, 1, 5, 6, etc.) distributes data over all disks. 303. 3 Things I Learned Building My First Neural Network I’ve been working with massive data sets for several years at companies like Facebook to analyze and address operational challenges, from inventory to customer lifetime value. But I hadn’t worked yet on something this ambitious. 304. Database Vs Data Warehouse Vs Data Lake: A Simple Explanation A data lake is totally different from a data warehouse in terms of structure and function. Here is a truly quick explanation of "Data Lake vs Data Warehouse". 305. It’s in the Data: How COVID-19 is Affecting the Digital Landscape I’m sure almost everyone reading this has been affected by the emergence of the novel coronavirus disease (COVID-19), in addition to noticing some serious disruptive economic changes across most industries. Our data research department here at Oxylabs has confirmed these movements, especially in the e-commerce, human resources (HR), travel, accommodation and cybersecurity segments. 306. How to Scrape Data from Google Maps Want to scrape data from Google Maps? This tutorial shows you how to do it. 307. 3 Top Resources To Learn About Apache Kafka Top 3 books and tutorials on Apache Kafka 308. 5 Big Data Trends for the Post-Pandemic Future As the digital landscape continues to expand at a mind-boggling pace, the amount of data stored and used by enterprises also increases. Over the course of recent years, the accumulation of big data within organizations has slowly but surely, established itself as a staple within companies, particularly as far as generating data-driven insights and upholding security. 309. Automated Data Catalogs will Help Manage Data in 2022 Data is increasingly playing a dominant role in business. Know how automating your data catalog can help with efficient data management in 2022. 310. Compete on Data Analytics using Spring Cloud Data Flow Data Driven 311. How Big Data Reshapes the Future of Digital Advertising - 3 Examples These days, big data is truly omnipresent. According to revenue forecasts, by 2026, big data volumes are expected to reach a whopping $92 billion. What August 2019 CMO Survey goes on to say is that the majority of ad tech and martech leaders agree - big data and innovative technologies are two pillars on which their marketing strategies are based. Businesses use big data in order to develop a detailed portrait of each segment of their customer base and apply these marketing strategies properly. 312. Introducing the Swahili News Dataset for Topic Classification Swahili (also known as Kiswahili) is one of the most spoken languages in Africa. It is spoken by 100–150 million people across East Africa. Swahili is popularly used as a second language by people across the African continent and taught in schools and universities. In Tanzania, it is one of two national languages (the other is English). 313. 13 Best Datasets for Power BI Practice In 2022, Gartner named Microsoft Power BI the Business Intelligence and Analytics Platforms leader. These are the 13 Best Datasets for Power BI Practice. 314. Using Artificial Intelligence and Big Data To Deliver Your Pitch A good pitch tells the story of your idea. From its inception to its present form and everything in between. Utilising multimedia, graphs and visuals is a good way to keep your audience engaged and up to speed. Most fundamentally, using data is important for both your audience and your idea. 315. How The 5th Wave Of Computing And IoT Are Changing Our Lives According to the World Economic Forum, in 2020 the entire digital universe has reached 44 Zetabytes of Data. 316. The Future of Human In The Loop Since the 1980’s, human/machine interactions, and human-in-the-loop (HTL) scenarios in particular, have been systematically studied. It was often predicted that with an increase in automation, less human-machine interaction would be needed over time. Human input is still relied upon for most common forms of AI/ML training, and often even more human insight is required than ever before. 317. Small Businesses use AI Tools to Increase Their Leads By 50% AI can empower sales reps by monitoring different signals and predicting a specific lead's readiness to purchase. AI tools can reduce customer acquisition costs 318. How To Meaningfully Interpret COVID-19 Data 319. The API to Bootstrap Your Flink Jobs Has Arrived Apache Flink is one of the most versatile data streaming open-source solution that exists. It supports all the primary functions of a typical batch processing system such as SQL, Connectors to Hive, Group By, etc. while providing fault-tolerance and exactly-once semantics. Hence, you can create a multitude of push-based applications using it. 320. 7 Challenges in Marketing AI & Machine Learning Solutions This article will help our readers to identify and understand the challenges faced by the AI development companies to market the AI & ML products. 321. BigData Behind Blockchain Forensics It seems a week doesn’t go by without more news of another cryptocurrency hack, fault, failure, scam, or what have you. Just this week saw EOS have a hacker lift $7.7 million in EOS after a mistake by one of their validators. You will often hear about how these types of transactions get resolved later, but not a lot of information is provided about how that happened. Last week I saw the news that controversial Italian surveillance vendor Neutrino was acquired by Coinbase (which Coinbase has already come to regret) and when I read up on them, I realized that it was companies like Neutrino that are able to help repair those hacks, track down the terrorist funding, ransomware, the gun running, and drug sales and other nefarious activity that can take place on blockchain. This led me to research the companies in this space and the one that looked the most robust to me was CipherTrace and speaking with CEO and co-founder Dave Jevans to find out more about what they do and how they do it. 322. Why Data Privacy is Important for Users in the Web3 Ecosystem Interview discussing why data privacy is important for users in the web3 ecosystem 323. Getting to Know Google Analytics 4: Four Smart Features You Don’t Know About Let’s take a deeper look into Google Analytics 4 and explore some of its key features that you might not yet know about. 324. How to Build Machine Learning Algorithms that Actually Work Applying machine learning models at scale in production can be hard. Here's the four biggest challenges data teams face and how to solve them. 325. How Big Data and Computers Leveled Up India in the 1950s When we think of computers, we think of the twenty-first century. But did you know that India started using them back in the 1950s? 326. How to Get Qualified to Work in Big Data for Decision Intelligence Decision intelligence, Data Stories, and Data Cloud Services are the three trends that are ranking high in the Data Analytics 2021. 327. 10 Most Evolving Big Data Technologies to Catch Up on in 2022 At the heart of it all, big data also has a dark side. Several tech giants are facing heat from the public and government regarding the issue of data privacy. 328. A Brief Introduction to Recommendation Systems Recommendation systems offer relevant product suggestions to users by using machine learning based on data gathered. More so,it uses characteristics information 329. How Important is the API Economy for Blockchain Application Development? A blockchain cannot take care of all the information it handles. It should focus on its core capability blockchain and not about providing different data options. 330. Data Scientists, Software Engineers And The Future of Medicine The world is changing, especially the way we cure ourselves. The rise of next generation computing, cloud computing technologies, AI, decentralization, etc. have dramatically changed seemingly every industry. Computational Medicine is now an emerging new discipline. 331. Universal Data Tool: New Skeletal/Pose/Landmark Annotation, Dutch, and Convert Options For those who haven’t heard of the Universal Data Tool, it is an open-source web or desktop program to collaborate, build and edit text, image, video, and audio datasets with labels and annotations. 332. Solving Data Integration: The Pros and Cons of Open Source and Commercial Software There was an awesome debate on DBT’s Slack last week discussing mainly two things: 333. Hadoop Data Storage Explained Explore how exactly distributed storage works in Hadoop? We have to characterize an essential node (known as NameNode) from one of the workers (DataNodes). 334. 20 Herramientas de Inteligencia Empresarial (BI) más Populares en 2020 Business Intelligence (BI) es un negocio basado en datos, un proceso de toma de decisiones basado en datos recopilados. A menudo es utilizado por gerentes y ejecutivos para generar ideas procesables. Como resultado, BI siempre se conoce indistintamente como "Business Analytics" o "Data Analytics". 335. Get Machine Learning Training Data Using The Lionbridge Method [A How-To Guide] In the field of machine learning, training data preparation is one of the most important and time-consuming tasks. In fact, many data scientists claim that a large portion of data science is pre-processing and some studies have shown that the quality of your training data is more important than the type of algorithm you use. 336. Sustainable Computing beyond the Cloud Extreme increases in data streams are expanding the cloud's carbon footprint; a sustainable alternative to Cloud dependence has been developed. 337. Machine Learning Trends Businesses Should Know In 2020 Have you ever considered how much data exists in our world? Data growth has been immense since the creation of the Internet and has only accelerated in the last two decades. Today the Internet hosts an estimated 2 billion websites for 4.2 billion active users. 338. Building a Data Management Strategy: Importance, Principles, Roadmap Already routinely called the currency, the lifeblood, and the new oil of the modern business world, data promises organizations unbeatable competitive advantages. 339. 5 Industries That Rock Big Data Analytics Each day we produce 2.5 EB of data [3]. This is 2.5 billion gigabytes of information about everything. This creates unlimited opportunities for collecting, processing, and analyzing vast amounts of both structured and unstructured data, also known as Big Data. 340. Getting Started with Data Visualization: Building a JavaScript Scatter Plot Module Scatter plots are a great way to visualize data. Data is represented as points on a Cartesian plane where the x and y coordinate of each point represents a variable. These charts let you investigate the relationship between two variables, detect outliers in the data set as well as detect trends. They are one of the most commonly used data visualization techniques and are a must have for your data visualization arsenal! 341. Top 6 CI/CD Practices for End-to-End Development Pipelines Maximizing efficiency is about knowing how the data science puzzles fit together and then executing them. 342. Why Microservices Suck At Machine Learning...and What You Can Do About It I've worked on teams building ML-powered product features, everything from personalization to propensity paywalls. Meetings to find and get access to data consumed my time, other days it was consumed building ETLs to get and clean that data. The worst situations were when I had to deal with existing microservice oriented architectures. I wouldn't advocate that we stop using microservices, but if you want to fit in a ML project in an already in-place strict microservice oriented architecture, you're doomed. 343. 3 Industries Harnessing the Power of Big Data: Healthcare, Law, and Retail Big Data's value, popularity, and scale of usage in business today come from a few of the indisputable benefits it has to offer: 344. Get Started With Big Data Analytics For Your Business. Everything we do generates Data, therefore we are Data Agents. The question is: how we can benefit from this huge amount of data generated every day?. 345. An Intro to Web Scraping: What it is and How to Start A quick introduction to web scraping, what it is, how it works, some pros and cons, and a few tools you can use to approach it 346. Ditching Big Tech for a More Decentralised Life With privacy and security issues, daily ransomware attacks putting sensitive data at risk of being published - I decided to de-Facebook and de-Google my life. 347. The Big Impact of Big Data on Businesses Today The business impact companies are making with big data analytics is driving investment in digital transformation across the board.Faced with multiple waves of disruption in a COVID-19 world, almost 92% of companies are reporting plans to spend the same or more on data/AI projects, according to a recent survey from NewVantage Partners.Small wonder.Data mature companies are citing business-critical benefits from using big data, including: 348. Lambda Architecture: A Comprehensive Introduction and Breakdown Big data is on the rise, and data systems are tasked with handling it. But this begs the question: Are these systems up for the task? 349. Blockchain and AI | A Disruptive Alliance AI and Blockchain are among some of the most influential drivers of innovation today — a natural convergence is occurring. 350. 10 Ways to Optimize Your Database Take these 10 steps to optimize your database. 351. Machine Learning Explained in 5 Minutes Google uses it to provide millions of search results every hour. It helps Facebook guess your next love interest. Even Elon Musk’s Tesla uses it to make self-dr 352. Data Privacy: Why The Existing Architecture is in Dire Need of Evolution Data is to the 21st century what oil was for the 20th century. The importance of data in the 21st century is conspicuous. Data is behind the exponential growth witnessed in the digital age. Increased access to data, through the internet and other technologies, has made the world a global village. 353. Machine Learning, 5G and Data Science Will be Critical to the Future of the Internet of Things By 2020, the total number of Internet-connected devices will be between 25-50 billion. 354. How to Use Big Data and Artificial Intelligence for Demand-Based Pricing in Retail You can call yourself a guru of retail pricing if you can make the right pricing decisions for every one of your products, separately and combined, based on their demand elasticity at any given moment. 355. How is Web Crawling Used in Data Science No-Code tools for collecting data for your Data Science project 356. What is Big Data in Healthcare and How is it Used? The pandemic is having an enormous impact on the healthcare sector. Between overwhelming hospitalization rates, intensifying cybersecurity threats, and an aggravating number of mental illnesses due to strict lockdown measures, hospitals are desperately searching for help. Big data in healthcare seems like a viable solution. It can proactively provide meaningful, up-to-date information enabling clinics to address pressing issues and prepare for what’s coming.Hospitals are increasingly turning to big data development service providers to make sense of their operational data. According to Healthcare Weekly, the global big data market in the healthcare industry is expected to reach $34.3 billion by 2022, growing at a CAGR of 22.1%.So, what is the role of big data analytics in healthcare? Which challenges to expect? And how to set yourself up for success? 357. Top Data Analyst Skills in 2021 Enhance your knowledge and skills in the field of data analytics with the help of data science certification for a rewarding career as a data analyst. 358. Allstate's Car Insurance Algorithm: How Insurance Algorithm Was Analyzed State regulators and consumer advocacy groups have scrutinized Allstate Corporation’s use of big data and personalized pricing in the way it calculates how much the company charges its private auto insurance customers. 359. Comparative Study Of Best Time-Series Models For Pandemic Response With the effect of the pandemic increasing every day and casting a vehemently toxic influence in almost all parts of the world, it becomes important how can we contain the spread of the disease. In an effort to combat the disease every country has increased not only their testing facility but also the amount of medical help and emergency and quarantine centers. Here in this blog, we try to model Single-Step Time Series Prediction, using Deep Learning Models, on the basis of Medical Information available for different states of India. 360. 5 Big Data Problems and How to Solve Them “Big Data has arrived, but big insights have not.” ―Tim Harford, an English columnist and economist 361. Deepfakes: Thy Expiration Date is Nigh Predictions that deepfake videos will keep getting better are not matched by the realities of the technology. Here's a sober look at the problems. Thank you for checking out the 361 most read stories about Big Data on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo