Let's learn about Big Data Analytics via these 89 free stories. They are ordered by most time reading created on HackerNoon. Visit the /Learn Repo to find the most read stories about any technology.
1. 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
2. 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...
3. Easily Integrate Embedded Analytics Into Your App
How to create performant embedded analytics with Tableau and Cube that are tailored precisely for your users, and do so efficiently and securely.
4. Top 6 Data Visualization Tools for 2022
In this blog you will discover best data visualization tools to effectively analyze your datasets. Learn about the tools to create intuitive visualization.
5. 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.
6. 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.
7. 10 Best Datasets for Geospatial Analytics (Open and Public Access)
Scientists use geospatial analytics to build visualizations such as maps, graphs and cartograms. These are the Best Public Datasets for Geospatial Analytics.
8. MongoDB: Exploring Data Visualization Tools and Techniques
Looking for MongoDB data visualization tool? There are plenty of options but firstly its better to explore what kinds of solutions there are on the market.
9. The New Frontier of Price Optimization
What would be the price of our product or service? This question has bothered businesses forever. Several pricing models have been spawned as a result. But the concept of price optimization is a fairly new one. At least to businesses that are not in the hospitality or airline sector.
10. 4 Tips To Become A Successful Entry-Level Data Analyst
Companies across every industry rely on big data to make strategic decisions about their business, which is why data analyst roles are constantly in demand.
11. Trends That Will Impact Data Analytics, AI, and Cloud in 2023
As we enter 2023, the world of analytics, AI, and cloud is entering an exciting new phase, with a wide range of innovations and developments set to reshape the
12. 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
13. Introduction To AWS Lake Formation
What does it mean for your organization?
Amazon Web Services (AWS) recently announced, among many other important updates, the release of the new service “AWS Lake Formation” at the AWS re:Invent in Las Vegas. This article provides a brief explanation of what the service does. Furthermore, it explains why it can be important for your organization.
14. Common MS Excel Questions to Help you Excel in a Data Analyst Job Interview
EXCEL Interview Questions for Data Analysts
15. How to Set Up a Dedicated Database Server for Analytics
Have that old laptop that's just in the back of your closet? Figure out how to give it a new life!
16. Growing Data Infrastructure Complexities: Cost Implications and the Way Forward
A deep dive into the journey of data infra– from traditional databases to the Modern Data Stack as it exists today, challenges in scaling, and upcoming trends
17. 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.
18. 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.
19. 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.
20. Data Teams Need Better KPIs. Here's How.
Here are six important steps for setting goals for data teams.
21. 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.
22. 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
23. 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.
24. SubQuery to Make Blockchain Data Easily Accessible on the Cosmos Blockchain
SubQuery is a blockchain developer toolkit that allows for web3 infrastructure through a custom open-source API between data and decentralized applications.
25. 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.
26. Comprehensive Data Analysis with SQL and Data Visualization: Alibaba User’s Behavior Investigation
This user behavior report is based on users’ orders from Alibaba between November 25th, 2017, and December 3rd, 2017 from the Alibaba platform...
27. 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.
28. Machine Learning Platforms Vs. Machine Learning Consulting Companies
There is no clear answer on whether or not it is better to use machine learning platforms or data consulting companies. Each company has different needs and financial resources.
29. My Prometheus is Overwhelmed! Help!
Your prometheus monitoring setup is grinding to a halt? You've thrown too much data at it? Don't worry, there's ways to fix this.
30. How a Data Scientist Sees a Deck of Cards
The Data Scientist Creativity Paradox
31. 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?.
32. 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
33. 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.
34. Fintech 2021: How Fintech Companies Use Big Data Effectively?
According to a study, 90% of the whole world’s data was created in the last two years. This sounds quite cool but what does the world do with all that data? How does one analyze it?
35. 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.
36. 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.
37. 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?
38. 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.
39. 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.
40. 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.
41. 5 DBT Repositories You Need to Star on GitHub
The 5 hottest dbt Repositories you should star on Github 2022 - Those are mine!
42. 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.
43. Behavioral Analytics: The Foundation of Targeted Marketing and Predictive Analytics
Learn how to capitalize on your business standards and increase the conversion rate by approximately 85% by analyzing customer behaviors with data you collect.
44. 8 Tools You Can Use to Analyze Big Data
An essential part of modern business, no matter what the industry, is Big Data - sets of copious amounts of data that reveal much in terms of trends and patterns regarding human behavior and interaction.
45. 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
46. How to Improve VC Deal Sourcing Using Public Web Data
Learn how public web data can help you improve your deal sourcing methods.
47. 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.
48. 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.
49. 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.
50. Data Integrity Is Vital for The COVID-19 Vaccine Rollout
This is why improving the processing and handling of COVID-19 and other health data should be a priority both during and after the pandemic.
51. 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.
52. Commoditized Data Integration And How To Achieve It
Most engineers in their professional life will have to deal with data integrations. In the past few years, a few companies such as Fivetran and StitchData have emerged for batch-based integrations, and Segment for event-based ones. But none of these companies have solved the problem of data integrations, which becomes more and more complex with the growing number of B2B tools that companies use.
53. What Are the Key Differences Between Qualitative and Quantitative Data?
This article uncovers the key differences between qualitative and quantitative data with examples.
54. Restructure or Recycle: Making the Right Data-driven Decisions
Understanding the difference between restructuring and recycling data allows analysts to make better-educated decisions.
55. 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
56. 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.
57. 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.
58. 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.
59. 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:
60. The Impact of Big Data In Business, Past and Future
Big Data: full-size disruptive
61. How Can The Travel Industry Benefit From Data Scraping
The travel industry is a major service sector in most countries these days. It is also a major employment and revenue provider. This demands a lot of constant innovation and maintenance. The travel industry is a dynamic industry where the needs and preferences of a customer change every moment. The market players in this field need to keep up with the trends in the industry, the choices of the customers and even on the details of their own historical performance to perform better as time progresses. Thus, as you would presume, the companies working in the travel sector need a lot of data from multiple sources and a pipeline to assess and use that data for insights and recommendations.
62. 5 Most Important Tips Every Data Analyst Should Know
The 5 things every data analyst should know and why it is not Python, nor SQL
63. Understanding the tech behind Snowflake’s IPO and what’s to come
By now you must have read quite a few articles about Snowflake’s absolutely mind-blowing and record-setting IPO. This article is not intended to speculate on whether the valuation makes sense or not, but rather help you understand the technological concepts that make Snowflake so unique, and why it has proven to be so disruptful for the data space in general and the data warehousing space in particular.
64. 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.
65. 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.
66. 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.
67. 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.
68. Can Big Data Solutions Be More Accessible And Affordable?
Below you can find the article of my colleague and Big Data expert Boris Trofimov.
69. 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?
70. 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.
71. 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.
72. How To Become A Data Scientist: Skills & Courses To Learn Data Science
The necessary skills to build a Data Scientist’s profile are business intelligence, statistical knowledge, technical skills, data structure, and more.
73. Accelerate Spark and Hive Jobs on AWS S3 by 10x with Alluxio as a Tiered Storage Solution
In this article, Thai Bui describes how Bazaarvoice leverages Alluxio as a caching tier on top of AWS S3 to maximize performance and minimize operating costs on running Big Data analytics on AWS EC2. The original article can be found on Alluxio's engineering blog.
74. 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.
75. 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.
76. How to Optimize Your Remote Workforce Using Big Data Analytics
Optimizing your remote workforce can easily be done using the help of big data analytics, as it can easily point towards time management issues and overwork.
77. 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.
78. Machine Learning for Fraud Prevention
Machine Learning aids e-commerce to foil attempts at payment fraud, as they happen.
79. Amazon Kinesis: The AWS Data Streaming Solution
Quick Guide of Amazon Kinesis which contains the Amazon Kinesis Introduction, Top Advantages & Use Cases of Amazon Kinesis.
80. 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.
81. 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)
82. 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.
83. 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.
84. I went on a Big Data Spree because of Covid19
Covid19 taken the world by storm. People have been panicking and buying toilet paper like no tomorrow. Celebrities have been making sure to keep us caught up on latest videos of them eating cereal. Anxious teens and twenty year olds have been extra moody.
85. Drowning in Information, Gasping for Knowledge
It is important to be able to correlate data from multiple disparate sources in different formats and types in a single display.
86. A Look at Big Data Architecture and its Components, Limitations and Advantages
As you might imagine, big data architecture is an overarching infrastructure that allows for the analysis of large data sets.
87. 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:
88. 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'
89. 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?
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