229 Stories To Learn About Data Analytics

Let's learn about via these 229 free stories. They are ordered by most time reading created on HackerNoon. Visit the to find the most read stories about any technology. Data Analytics /Learn Repo No matter the project, data analytics are a must. 1. Spotify Audio Features Time Series in Additive Spotify Analyzer There are many articles on analyzing Spotify data and many applications as well. Some are a one-time analysis on individual's music library and some are an app for a specific purpose. This app is different in that it does not do one thing. It is meant to grow and provide a place to add more analysis. This article is about how the audio features time series was created. 2. Data Lakehouses: The New Data Storage Model Data lakehouses are quickly replacing old storage options like data lakes and warehouses. Read on for the history and benefits of data lakehouses. 3. How Drones Are Transforming Big Data Analytics The world is transforming right before our eyes. We’ve heard about drones for a long time now, especially with big companies like Amazon using them for more efficient package delivery, a major trend in modern e-commerce. Instead of your local delivery man, a drone may drop a package right on your doorstep. The true power of drones goes well beyond that, though. They provide businesses with data that’s difficult to collect otherwise. In addition to taking aerial photos and videos, drones can collect information about everything from the health of crops to thermal leaks in buildings. 4. Use Up-Sampling and Weights to Address Imbalance Data Problem Have you worked on machine learning classification problem in the real world? If so, you probably have some experience with imbalance data problem. Imbalance data means the classes we want to predict are disproportional. Classes that make up a large proportion of the data are called majority classes. Those that make up a smaller portion are minority classes. For example, we want to use machine learning models to capture credit card fraud, and fraudulent activities happens approximately 0.1% out of millions of transactions. The majority of regular transactions will impede the machine learning algorithm to identify patterns for the fraudulent activities. 5. Promoting Indigenous Data Sovereignty through Blockchain in Canada How can Indigenous Sovereignty be upheld with modern technology? 6. How to Build a Data-Driven Product Using Metabase Metabase is a business intelligence tool that lets you access your data in a read-only manner. 7. My Favorite Free Excel Courses for Programmers, Data Analysts, and IT Professionals If you want to learn Microsoft Excel, a productivity tool for IT professionals, and looking for free online courses, then you have come to the right place. 8. Amazon Is Losing Market Share Across Several Segments to Competitors [A Numbers Game] You’ve probably read about how Amazon has put a stop to its paid acquisition. We’ve covered the topic extensively already over the past few weeks, and yet, what we’ve recently discovered sheds some light on the magnitude of this move. 9. Why Python Is Leading the Charge in Data Analytics Python is one of the oldest mainstream programming languages, which is now gaining even more ground with a growing demand for big data analytics. Enterprises continue to recognize the importance of big data, and $189.1 billion generated by big data and business analytics in 2019 proves it right. 10. Top 40+ Data Science Product Interview Questions Find the top 40+ product interview questions you must prepare for your next data science interview. 11. 5 Upcoming Online Machine Learning Conferences in 2020 Machine learning conferences have always played an important role in the world of data science. They're a place to announce new research, discuss current issues, and connect with the community. They also help to promote new areas of research and development through Q&A sessions, workshops, and tutorials. 12. 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. 13. Evolution of The Data Production Paradigm in AI The long-term success of an AI-based product relies on having the infrastructure for scalable, flexible, and cost-effective data labeling for its learning. 14. 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. 15. 4 Ways Cities Are Utilizing Data for Public Safety Cities have been using data for public safety for years. What new technology is emerging in public safety, and how does it affect you? 16. How to use Redis HyperLogLog How to use Redis HyperLogLog data structure to store millions of unique items. 17. Machine-Learning Neural Spatiotemporal Signal Processing with PyTorch Geometric Temporal PyTorch Geometric Temporal is a deep learning library for neural spatiotemporal signal processing. 18. The Qnum Analytics Team On Turning A Side Gig Into A Full Time Business The team behind Qnum Analytics, tool leveraging AI to help businesses fix leaky inventory buckets, shares their origin story and what makes their team special. 19. Reimagining What Visual Data Transformation Tools Should Look Like Data is not code. Professional analytics is not Python\SQL coding. We value our time, and time to value. Data people deserve the best tooling possible. 20. Why Professions Are Adding Analytics to Their Skillsets There are many different forms of data analytics, and these have different applications in business. 21. "Writing Routine Needs to be Fluid and Adaptable": Meet the Writer Alex Jivov, CEO of Hopeful Inc. Meet Alex Jivov, CEO of Hopeful Inc, and a person of many interests. Giving us more details into how a former journalist approaches the new writing routine. 22. Using Data Analytics Effectively in Marketing How to make your data work harder for you in marketing 23. 5 DBT Repositories You Need to Star on GitHub The 5 hottest dbt Repositories you should star on Github 2022 - Those are mine! 24. KYVE Mainnet Goes Live on Pi Day, Opening The Doors To Truly Trustless Data In Web3 KYVE, the decentralized data lake, mainnet officially live, opening the doors to truly Trustless data in web3. 25. Are You Poisoning Your Data? Why You Should Be Aware of Data Poisoning As machine learning gains more prominence, these attacks may become more common. Here’s a closer look at data poisoning and what companies can do to prevent it. 26. How Did You Become A Data Scientist? Every data professional has a unique story as to how they entered the field of data science. Here is my career path origin story. 27. 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. 28. Create a Search Engine and Other Startup Ideas Using Data-Ferret Data-ferret is a tiny, yet powerful util library to scan or transform deeply nested and complex object-like data with ease. 29. Hack Your Way to LookML Mastery By Following These Tips Tips to help BI developers create a seamless pipeline in Google's visualization tool Looker. 30. How to Improve VC Deal Sourcing Using Public Web Data Learn how public web data can help you improve your deal sourcing methods. 31. Is The Modern Data Warehouse Dead? Do we need a radical new approach to data warehouse technology? An immutable data warehouse starts with the data consumer SLAs and pipes data in pre-modeled. 32. How to Grow your Video Business with Data TV watching used to be a family affair a decade ago, but today in most households, content watching has become a personal activity. 33. How Retailers Can Leverage Personalization to Drive Customer Centricity in the Metaverse Era The next frontier for personalization at scale is in VR and AR, and the next frontier of retail is consumer-first 34. Six Habits to Adopt for Highly Effective Data Put your organization on the path to consistent data quality with by adopting these six habits of highly effective data. 35. Understanding the Differences between Data Science and Data Engineering A brief description of the difference between Data Science and Data Engineering. 36. 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. 37. 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! 38. Optimize Power BI Reporting and Designing As a data analysis tool, Power BI comes loaded with plenty of report generation and design features. However, do not rely on the default settings of the tool. 39. How To Deploy Metabase on Google Cloud Platform (GCP)? Metabase is a business intelligence tool for your organisation that plugs in various data-sources so you can explore data and build dashboards. I'll aim to provide a series of articles on provisioning and building this out for your organisation. This article is about getting up and running quickly. 40. 7 Data Analysis Steps You Should Know To analyze data adequately requires practical knowledge of the different forms of data analysis. 41. 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? 42. What Working on an Analytics Product Can Teach Us About Data The ubiquity of analytics hides potential complexity underneath, especially when you start to consider products where the analytics are more front and centre. 43. What is the Future of the Data Engineer? - 6 Industry Drivers Is the data engineer still the "worst seat at the table?" Maxime Beauchemin, creator of Apache Airflow and Apache Superset, weighs in. 44. Watch Out for Deceitful Data Nowadays, most assertions need to be backed with data, as such, it is not uncommon to encounter data that has been manipulated in some way to validate a story. 45. Customer Data Platform (CDP) Vs Data Warehouse, CRM, and Data Management Platform In this post, we highlight some key differences between a Customer Data Platform (CDP) and other tools generally used in a marketing tech stack. We also tackle the all-important question on many companies’ minds: “should I build or buy a CDP?.” 46. 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". 47. Size Does Matter: Global Control Group for a Bank Learn how to approach data-driven measurement properly. See what unexpected results we got in a bank and get insights for your own data analytics journey. 48. What Are the Key Differences Between Qualitative and Quantitative Data? This article uncovers the key differences between qualitative and quantitative data with examples. 49. 5 Most Common Data Quality Issues For Business With the advent of data socialization and data democratization, many organizations organize, share and make information available to all employees in an efficient manner. While most organizations benefit from liberal use of such a source of information available to their employees, others struggle with the quality of the data they use. 50. The Essential Skills Every Marketer Needs This article will help you understand the demand for digital marketing and the skills you will need to enter a digital marketing career 51. Practical Tips to Improve Customer Experience with Data According to a report, almost 70% of companies compete on customer experience. 52. 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. 53. Polygon data: What it is and how can it be used? This blog explains about polygon data, its benefits and how it is widely used in geomarketing, indoor mapping, and mobility analysis for orgnaizations. 54. How to Create a Data Analytics Strategy to Grow Your Business Are you building a Software-as-a-Service platform? Wondering what data is essential for your business? Time for a Data Analytics Strategy. 55. 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! 56. How Data-Driven Coaching Helps Employees Reach Their Potential Data is everywhere. In the business world alone, we use it to track search engine traffic, monitor website activity, land sales, improve customer service. 57. Data Science With R Programming — Coding Interview Questions R is a tool used for data management, storage, and analysis in the field of data science. It has applications in statistical analysis and modeling. 58. The Most Commonly Used SQL Queries by Data Scientists SQL (Structured Query Language) is a programming tool or language that is widely used by data scientists and other professionals 59. 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. 60. Why AI is the Future of Restaurant Sales Think about all of the things you could do with unlimited data and insights about your sales. Now, think about all of the things you could do with future data and insights about your sales? 61. 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? 62. Capturing Trends in HealthCare at 1mg (E-pharmacy Unicorn) Recommendation in Healthcare with simple analytics to show most trending products on the platform. 63. Why Businesses Need to Take Full Advantage of IIOT and Data Analytics Modern business is driven by digital technology, and yet many business leaders remain hesitant to adopt them. 64. 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. 65. Solving Noom's Data Analyst Interview Questions Noom helps you lose weight. We help you get a job at Noom. In today’s article, we’ll show you one of Noom’s hard SQL interview questions. 66. Useful Digital Tools for Nonprofit Attorneys We've identified some potential pain points for nonprofit attorneys, where a lack of effective tech can slow down processes or leave holes in security practice. 67. 5 Ways to Become a Leader That Data Engineers Will Love How to become a better data leader that the data engineers love? 68. Applying Criminology Theories to Data Management: "The Broken Window Theory: and "The Perfect Storm" What can be done to prevent “Broken Windows” in the primary data source? How can we effectively fix existing “Broken Windows"? 69. Ensuring Security in Your SaaS Applications [An Overview] Enterprises are constantly faced with the task of balancing the advantages of productivity gains and lower costs against significant compliance and security concerns as they move their data and applications to the cloud. 70. What is Data Analytics and How It Can Be Used WHAT IS DATA ANALYTICS? 71. 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. 72. The Art of Data Storytelling: How to Make Your Data Impactful Data is everywhere: whether you choose a new location for your business or decide on the color to use in an ad, data is an invisible advisor that helps make impactful decisions. With quite a number of resources to choose from, data is becoming more accessible, day by day. But as soon as it has been collected, one inevitable question arises: how do I turn this data into insights that can be acted upon? 73. Data-Driven Validation for Business Ideas: A Step-by-Step Guide Unlock the potential of data-driven validation for your side project. Discover how utilizing data insights drives informed decision-making and save some grief! 74. Don't Be Data-Driven. Become Purpose-Driven and Data-Assisted. 75. 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. 76. 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. 77. The Operational Analytics Loop: From Raw Data to Models to Apps, and Back Again Over the next decade or so, we’ll see an incredible transformation in how companies collect, process, transform and use data. Though it’s tired to trot out Marc Andreessen’s “software will eat the world” quote, I have always believed in the corollary: “Software practices will eat the business.” This is starting with data practices. 78. Tableau Vs. Power BI: The Complete Comparison The world of analytics is continually evolving, introducing new goods and adjustments to the modern market. New companies are entering the market and well-know 79. Web Scraping Google Maps Reviews In this post, we will learn to scrape Google Maps Reviews using the Google Maps hidden API. 80. Statistics Cheat Sheet: A Beginner's Guide to Probability and Random Events A beginner’s guide to Probability and Random Events. Understand the key statistics concepts and areas to focus on to ace your next data science interview. 81. 23andMe and Other Sites are Selling Users' Genetic Data: How Safe is Your DNA? How genetic information from sites like 23andMe and Ancestry.com is being shared and sold. 82. Top Tableau Consulting Companies on the Market in 2020 Business intelligence has become an indispensable part of successful businesses, and the sooner executives recognize data as a crucial component of decision-making, the sooner they will be able to improve their operational processes. 83. AI and Machine Learning for Manufacturing Industry: Use Cases Artificial Intelligence(AI) has already proven to solve some of the complex problems across the wide array of industries like automobile, education, healthcare, e-commerce, agriculture etc. and yield greater productivity, smart solutions, improved security and care, business intelligence with the aid of predictive, prescriptive and descriptive analytics. So what can AI do for Manufacturing Industry? 84. What the Heck Is Malloy? Malloy is a new experimental language for describing data relationships and transformations created by the developer of Looker. 85. Creativity in Data Analytics is About More than Data Visualization I recently attended a networking event where I spoke to a range of graduates who were looking at prospective careers in the data science and adjacent spaces. 86. 2020: Our Meatless, Cashless, City-less Future Happy New Year! 2019 has come and gone like Kylo Ren’s reign in The Rise of Skywalker, and so it's time for my annual prediction piece. 87. 3 Ways You Can Build and Update Websites Using Data Pushes Data is getting more and more accessible and is increasingly being used to inform the way businesses operate. 88. A Step By Step Guide To Data Visualization With Power BI Power BI is the collective name for an assortment of cloud-based apps and services that help organizations collate, manage and analyze data from various sources 89. 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! 90. 5 Best Practices for Tracking In-app Event Data This is the era of mobile apps. We get everything - from critical business information to entertaining videos and games - on our mobile devices. Information is right at our fingertips, and we are always striving to catch up with the outside world. As per App Annie, an average smartphone user has 80 apps installed. 91. Applications of Predictive Analytics in your Recruitment Journey Elanor is an HR executive at Unicorn marketer. She’s been involved in the recruitment process for six years now. Every year they do a campus drive at the most prestigious college in Chicago. They’re always on the look for a promising candidate for a challenging role as a Digital Marketer. Elanor has been maintaining a spreadsheet of rejected candidates for the same post and logging the reasons for rejection as well. 92. Mean Reversion Trading Systems and Cryptocurrency Trading [A Deep Dive] Prices move in a wave like fashion, moving back and forth following a broader trend. While doing so, it often revolves around a mean. It might move across or bounce off the mean. Mean reversion systems are designed to exploit this tendency. 93. So You Just Became a Data Science Manager... Now What? With the rise of data science there has been the rise of data science managers. So what do you need to keep in mind if you wish to join these data translators that are acting as a conduit between the business and technical data teams? Going from a practitioner to a manager — your job now is to make sure that data resources are being used optimally so how do you go about doing this effectively? 94. Scraping Google Search Results With Node JS In this post, we will learn web scraping Google with Node JS using some of the in-demand web scraping and web parsing libraries present in Node JS. 95. How to Create a Simple Web Dashboard for Efficient Data Analytics Dashboard with different visualizations allows you to compare data and show changes and tendencies. In this tutorial I wil explain why and how to build one. 96. 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 97. 5 Best Data Curation Tools for Computer Vision in 2021 In this article, we’ll dive into the importance of data curation for computer vision, as well as review the top data curation tools on the market. 98. 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. 99. Top 6 Mobile Analytics Tools of 2020 Data has become an increasingly important factor when it comes to the health of any app or website. Having all of your important numbers such as the number of downloads, amount of money generated from downloads and even the most recent feedback is the key to continued success. 100. Beyond Artificial Intelligence: Providing Insights to Your Customers 101. How to Scrape Data from Google Maps Want to scrape data from Google Maps? This tutorial shows you how to do it. 102. Which Database Is Right For You?Graph Database vs. Relational Database Learn about the main differences between graph and relational databases. What kind of use-cases are best suited for each type, their strengths, and weaknesses. 103. Data-Driven Approach for Software Engineering: How to Avoid Common Problems In today’s digital world, data is constantly being generated, evaluated, and updated. It also plays an important role in the work of software engineers by providing accurate, actionable feedback that helps engineers understand where and how to make improvements to a product or process. 104. Deep Dive Into Open Source BI Tool Helical Insight When Helical Insight first announced a couple of years ago that they were releasing an Open Source Business Intelligence (BI) tool, it really caught my interest and I reached out to founder Nikhilesh Tiwari to find out more about what he was doing. I spent a little time with the product and really liked where it was going and was determined to do more of a deep dive in the future, and with their release of version 3.0, that time is now. 105. 8-Ways Data Mining Can Improve your Business If your company is trying to make sense of the customer data, here’s a not-so-surprising fact for you. You aren’t alone. Far too many companies want to understand data and gain an in-depth insight into the information they are sitting on. Let’s be clear that today, the success of a business lies in how efficient their data mining process is. Their expertise to process the available data as this can help them to decipher age-old questions that make or break them: 106. My Weird Career Transition From MBA to Data Science Yes you read it correctly! I am calling my transition from being an MBA to being the Analytics Manager in a well known consumer retail brand a "WEIRD" one. And why do I say that? Because during my 5 year journey in data science, I have had the opportunity to work with a lot of business stakeholders like marketing head, brand managers, sales heads etc. and many a times they have asked me about my educational background. I would like to think that they asked this because of my ability to present the solutions keeping the business context and execution feasibility in mind. Well, the reason for asking this might be different for every individual, when I tell them that I am an MBA, their reply has always been the same, which is "What made you choose a technical career path after pursuing MBA?" And hence I decided to write this post to share my thoughts over 2 things: 107. Creating an Interactive Word Tree Chart with JavaScript Learn how to create beautiful interactive JavaScript Word Trees and check out an awesome Word Tree chart visualizing the text of The Little Prince. 108. 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. 109. 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. 110. Data Science From Scratch Data Science, which is also known as the sexiest job of the century, has become a dream job for many of us. But for some, it looks like a challenging maze and they don’t know where to start. If you are one of them, then continue reading. 111. How to Consolidate Real-Time Analytics From Multiple Databases Have you ever waited overnight for that report from yesterday’s sales? Or maybe you longed for the updated demand forecast that predicts inventory requirements from real-time point-of-sale and order management data. We are always waiting for our analytics. And worse yet, it usually takes weeks to request changes to our reports. To add insult to injury, you keep getting taxed for the increasing costs of the specialized analytics database. 112. Restructure or Recycle: Making the Right Data-driven Decisions Understanding the difference between restructuring and recycling data allows analysts to make better-educated decisions. 113. Software Development for the Nuclear Industry One of the biggest problems facing leaders in the nuclear energy industry is the aging infrastructure in the United States and abroad. 114. Compete on Data Analytics using Spring Cloud Data Flow Data Driven 115. Planning for Your Startup: The Data Team's Guide to 2021 Planning in a startup can feel like an exercise in futility — especially when it comes to data — especially when your data team is small and scrappy. 116. How to Track User Navigation Events in a React Application A scalable and maintainable strategy for tracking page navigation events in a React application. 117. 3 Best Ways To Import External Data Into Google Sheets [Automatically] Google Sheets is a great tool to use for business intelligence and data analysis. If you want to eliminate manual data imports and save time, then let me will show you how you can automatically connect and import data from external sources into Google Sheets. 118. What Are the Most Common Mistakes Made by Aspiring Programmers? I wasted A LOT of my time teaching myself the basics of coding, machine learning, and stats. 119. Secure Multi-Party Computation Use Cases Secure Multi-Party Computation (SMPC), as described by Wikipedia, is a subset of cryptography to create methods for multiple users to jointly compute a function over their inputs while keeping those inputs private. A significant benefit of Secure Multi-Party Computation is that it preserves data privacy while making it usable and open for analysis. 120. 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. 121. How Advanced Data Analytics is Impacting B2B Sales Machine Learning and data analytics have shown a pronounced effect on various aspects of the commercial world and industries. Enterprises are using innovation in the field of data analytics and machine learning to design better marketing campaigns. It also helps generate pricing and customer-centric recommendations and even plan more effective financial budgets. 122. The Rise of Reusable SQL-based Data Modeling Tools and DataOps services The resurgence of SQL-based RDBMS 123. Data and Analytics Predictions for 2020 [A Top 5 List] It would be no exaggeration to say that the capacity of technology to advance itself is proceeding at a faster rate than our ability to process these changes all at the same time. This is both amazing and alarming in the same breath. 124. 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. 125. COVID-19: We Need More Than Data, We Need Insights! TL;DR We are managing the pandemic situation only with part of the data and not necessarily representative of reality. We must take a census of the number of positive and negative cases within a population. The officially reported positive cases contain a bias: they are cases that already manifest the disease in a more or less serious way. In the long term, the strategy of aggressive testing (South Korea model) is the only viable and sustainable to manage coexistence between the virus and the human beings until a vaccine will be available. 126. The Importance of Sports Analytics You’re probably familiar with the movie Moneyball (if not, watch it!). It’s the story of Billy Beane, the former MLB player and manager of the Oakland A’s, a struggling team with one of the smallest budgets in the league. Using statistical analysis methods, he ditched all traditional advice and based recruitment purely on data. The result? The A’s won 20 consecutive games, the first team in over a century to do so. 127. 3 Best Ways To Import JSON To Google Sheets [Ultimate Guide] 3 ways to pull JSON data into a Google Spreadsheet 128. Analyzing Dogecoin Tweet Sentiment in Real Time How to analyze Dogecoin tweet sentiment in real-time with a new managed Kafka platform. 129. High-Utility DeFi Data Analytics Tools For Crypto Investors These four growing platforms will give investors the tools they need to make smarter decisions 130. An Introduction to Data Connectors: Your First Step to Data Analytics This post explains what a data connector is and provides a framework for building connectors that replicate data from different sources into your data warehouse 131. Scraping Data With Selenium: Upwork Series #2 Hi Devs! 132. 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 133. Secrets to Growth Marketing Data Engineering – Even in This Down Economy Marketing is a big business and it's only going to grow bigger. One reason for this is that marketers need to keep growing the list of data points. 134. Data-Driven Talent Management: The Long Road Ahead While we’ve been long reliant on computers and the internet to work and collaborate, an entirely officeless organization is a recent notion. 135. 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. 136. 6 Reasons to Use Amazon Redshift A quick guide to Amazon Redshift's benefits and use cases. Learn why your team might want to make the SHIFT to Amazon Redshift. 137. The Role of AI and ML in Enhancing The Ability Of Multiplying Wealth Landing a good job is generally considered the purpose of education today. 138. 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. 139. A JavaScript Infographic: Data Science Salaries in 2022 Data visualisation infographic with insights on salary level of data scientists - how to create the JavaScript dashboard and analyse its data 140. 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. 141. 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. 142. New Power BI Features For More Streamlined Data Analysis Here are the new features of Power BI (unveiled at the Microsoft Ignite 2021) that can be absolutely beneficial for business users. 143. 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. 144. 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. 145. 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. 146. A Look into the History and Future of Web Analytics Today, web analytics are an important part of how millions of businesses operate. Businesses of all sizes and stripes rely on services like Google Analytics to help them understand consumer wants and optimize web experiences for them. Data analytics is a rapidly growing field as well, expected to be worth $550 billion by 2028. 147. '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. 148. Privacy Enhancing Technologies: Top 3 Use Cases Security and risk management leaders can apply privacy-enhancing tech in AI modelling, cross-border data transfers, and data analytics to manage constraints. 149. What the Heck is PRQL? Another clever tool for a powerful SQL pre-processor 150. 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! 151. Analyzing Data: What Are Text Mining and Text Analytics? What are text mining and text analytics? 152. 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 153. How Datadog Revealed Hidden AWS Performance Problems Migrating from Convox to Nomad and some AWS performance issues we encountered along the way thanks to Datadog 154. Moving From the Flat Earth: Why We Should Switch to Data-Driven Finance Businesses should switch from linear formulae to data-driven finance. This will allow companies to not only get an immediate revenue boost! 155. 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 156. How Color Psychology Impacts Branding While there is still much research to be done, color psychology has been used in fields such as marketing and design to help create appealing appealing products 157. 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 158. 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? 159. 6 Pitfalls to Avoid When Transitioning To a Data Science Career If you are considering the transition to a data science career these are common mistakes and traps you'll want to avoid. 160. How to Define Data Analytics Capabilities Disclaimer: Many points made in this post have been derived from discussions with various parties, but do not represent any individuals or organisations. 161. How Data Analytics is Changing the Restaurant Industry The integration of POS and advanced analytics help businesses get to the best, single view of separate customers needs across different restaurant outlets. 162. Intro to AI Analytics and Top 5 Use Cases for Businesses Analytics works by extracting meaningful patterns in data and interpreting and communicating them. 163. 5 Reasons to Invest in Analytics For Your Startup Now Data analytics are a startup's best friend, and here are five reasons why. 164. 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. 165. 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. 166. How to Improve Social Media Campaign Using Data Visualization Learn what social media data visualization is and why it is important. 167. The Independent Phone : More Privacy, Less Freedom? Freedom and privacy tend to go together, but there is a difference. With a more private phone, does it really mean you have more freedom? 168. The Importance Of Data in Sales in 2022 169. 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. 170. An Intro to User Analytics in the Gaming Industry Gaming analytics can be best defined as is the whole process of applying user behavior data to guide sales & marketing, product enhancements, etc 171. Executing a T-test in Python In today’s data-driven world, data is generated and consumed on a daily basis. All this data holds countless hidden ideas and information that can be exhausting 172. Common MS Excel Questions to Help you Excel in a Data Analyst Job Interview EXCEL Interview Questions for Data Analysts 173. 10 Best Datasets for Time Series Analysis In order to understand how a certain metric varies over time and to predict future values, we will look at the 10 Best Datasets for Time Series Analysis. 174. Top 3 Things You Forget When Building Your SaaS Product While the number of product management roles in the US has grown by more than 30% in two years, according to LinkedIn, the responsibilities of the job are morphing. 175. 6 Ways to Increase Revenue in 2020 with Market Intelligence Data Data analytics tools are increasingly being used in businesses, but many people still make critical decisions based on assumptions and guesses. The most common reason for this is the lack of a single, integrated source of information that gives executives accurate and consistent data whenever needed. 176. How AI and Data Analytics Will Impact The Era of COVID-19 Artificial intelligence (AI) and data analytics are rapidly growing trends in the tech world. With increasing potential for innovation, it is paramount that we stay up to date with all the latest developments in this field. According to MarketsandMarkets, the worldwide artificial intelligence (AI) market will increase from USD 58.3 billion in 2021 to USD 309.6 billion by 2026, at a compound annual growth rate (CAGR) of 39.7 percent over the projected period. It seems that every company wants a piece of this growing pie. By 2022 it is expected that 90% of companies will be using some form of artificial intelligence for data analytics purposes. 177. Metrics, logs, and lineage: 3 Key Elements of Data Observability Data observability is built on three core blocks: metrics, logs, and lineage. What are they, and what do they mean for your data quality program? 178. 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. 179. What You Need to Consider When Hiring a Data Scientist Dubbed “the sexiest job of the 21st century” by the Harvard Business Review, the demand for data scientists has grown dramatically. The number of job postings for this career increased by 31% from December 2017 to December 2018. And over the course of the last 6½ years, postings have surged by a staggering 256%. 180. Merging Datasets from Different Timescales One of the trickiest situations in machine learning is when you have to deal with datasets coming from different time scales. 181. How Smart Analytics Can Help Small Businesses Boost Sales Technology has taken over the world, now is the time for small businesses to realize that what they need is tech. Smart analytics makes everything easier. 182. Self-Service Business Intelligence and How to Do It Properly Self-service business intelligence, or BI, has been on the to-do list of many organizations for quite a while. 183. Hacking Your Analytics: Top Barriers in Harnessing the Power of Data An infographic to take a look at how to use more of your organization's data with Google Analytics 360 to form solid data based business decisions proactively. 184. Using Data Analytics for Unhindered Business Growth Every business, regardless of the size and spread, requires data analytics support to thrive. These Top Data Analytics Trends will help you grow your business. 185. Staying Ahead Consistently with Competitive Pricing Intelligence Business is looking good, you are making decent profit margins each year, and your customers seem to be happy with your services. 186. Accelerating Analytics by 200% with Impala, Alluxio, and HDFS at Tencent This article describes how engineers in the Data Service Center (DSC) at Tencent PCG (Platform and Content Business Group) leverages Alluxio to optimize the analytics performance and minimize the operating costs in building Tencent Beacon Growing, a real-time data analytics platform. 187. HarperDB is More Than Just a Database: Here's Why HarperDB is more than just a database, and for certain users or projects, HarperDB is not serving as a database at all. How can this be possible? 188. Things to Consider When Looking For Data Science Roles There is a great demand for data scientists presenting market dynamics that are favourable for the community. More so than your peers in other professions, you will be able to evaluate a company for what it is able to offer you, rather than solely being the one that is being evaluated. So what should you look for when comparing and evaluating data science roles? Here is a list of some commonly known factors plus some less discussed ones that will help you in your evaluation. 189. "Connect, Analyze and Learn from Data" - Dr. Yu Xu Welcome to "Mondays with Entrepreneurs". This week we have with us an Entrepreneur and tech expert who thinks Monday is the most exciting day of the week. 190. How Self-Service Analytics Creates a Major Shift In Product Mindset Interview with Amir Movafaghi, CEO at Mixpanel and ex-Twitter VP, where we discuss why self-service analytics is here to stay as a driver of product-led growth. 191. Creating A Data Science Pipeline That Works Correctly An easy, automated, repeatable way to check your data science solution is doing exactly what it's designed to do. 192. Data Journalism 101: 'Stories are Just Data with a Soul' Gone are the days when journalists simply had to find and report news. 193. Automate Submissions for the Numerai Tournament Using Azure Functions and Python Python Automation with Azure Functions, to compete in the weekly Numerai tournament. 194. What Is Modern Business Intelligence? This article gives insight into some basic features and functionality that a desirable modern BI software has and illustrated some examples. 195. 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 196. An Introduction to Data Automation for Business Efficiency In today’s competitive business landscape, data automation has become necessary for business sustainability. Despite the necessity, it also comes with a few challenges--collecting, cleaning, andputting it together--to get meaningful insights. 197. How To Get Real-Time Analytics By Consolidating Databases Benchmark a Hybrid Transactional and Analytical RDBMS (Photo: Sawitre) 198. Secure Enclaves and ML using MC² Announcing the official release of MC², a platform for secure analytics and machine learning. 199. Using User Data After Google's Third-party Cookies Ban Google announced that it would ban the usage of third-party cookies; it has made a lot of publishers afraid that they won't be able to utilize user data. 200. 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?. 201. Finding Digital Crimes by Exploring Master File Table (MFT) Records To explore the MFT records, learn how to locate date and time values in the metadata of a file we create. 202. 12 Best Pre-Installed R Datasets Commonly Used for Statistical Analysis R programming is mostly used in statistical analysis and ML. This article looks at the Best Pre-Installed R Datasets Commonly Used for Statistical Analysis. 203. 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? 204. 8 Best Human Behaviour Datasets for Machine Learning Human behaviour describes how people interact and in this article, we will look at the 8 Best Human Behaviour Datasets for Machine Learning. 205. 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' 206. 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 207. Digital Transformation Strategy: Dinosaurs, Harpoons, Greek Myths and YOU! Digital transformation is not one single thing to implement, it is a core alignment with continuous investment in innovation and excellence. 208. 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. 209. Why Businesses Need Data Governance Governance is the Gordian Knot to all Your Business Problems. 210. Alluxio Accelerates Deep Learning in Hybrid Cloud using Intel’s Analytics Zoo powered by oneAPI This article describes how Alluxio can accelerate the training of deep learning models in a hybrid cloud environment when using Intel’s Analytics Zoo open source platform, powered by oneAPI. Details on the new architecture and workflow, as well as Alluxio’s performance benefits and benchmarks results will be discussed. The original article can be found on Alluxio's Engineering Blog. 211. 6 Data Analytics Growth Hacks for SMBs Data analytics offers you amazing capabilities to grow your business. Leverage the power of these amazing data analytics hacks to reach your business goals. 212. How To Segment Shopify Customer Base with Google Sheets and Google Data Studio After defining what the RFM analysis is standing for, and how you can apply it to your Customer Base, I want to show you how to apply it on Shopify orders data. 213. How to See Areas in Your Organization Where Data can Make a Difference What is the first thing that you do when you start a new data science or analytics role? 214. 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. 215. Top 7 Use Cases of Predictive Analytics in Healthcare “I’ve never been able to predict the future of anything”, said Bob Edwards, one of the most accomplished American journalists. 216. AI Is Making Our Concrete Buildings And Bridges Safer AIs application to civil engineering and concrete construction is the future of structural safety. There have been various successful & innovative applications. 217. 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. 218. Privacy Protection and Web3 Analytics Though there have been more and more developers and product designers joining Web3.0 world in recent years, it is almost ignored by most of them that they are still using centralized infrastructure — data analytic tools — to build apps and webs. Every minute, project builders are making themselves part of the reason for data breach events, as they have to collect user data intendedly or unintendedly for product improvement. 219. A Brief Introduction Into A Typical Data Science Project Life Cycle In this post, I demystified data science and talked about the lifecycle of a typical data science project. It's a good read for everyone. 220. 5 Strategic Digital Transformation Domains for Your Small Enterprise The digital era has largely changed how we do business. 221. 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. 222. How To Build a Data-Savvy Brand Since new-gen tech has enabled companies to mine large sets of structured and unstructured data, the idea of becoming a data-driven company has become the preoccupation of many executives. 223. Year of the Graph Newsletter, April 2020: Graphs Power Scientific Research; Business Cases Is there life after COVID-19? Of course there is, even though it may be quite different, and it may be hard to get there. But there’s one thing in common in the “before” and “after” pictures: science and technology as the cornerstones of modern society, for better or worse. 224. How To Choose The Right Business Intelligent Tool In this blog, we look at strategies for selecting the right BI tool as well as some important things to keep in mind throughout the process. 225. Data Scientist Careers at Amazon: What You'll Earn, Learn, and Work On Find out what it means to be a data scientist at Amazon! Their salaries, roles and required experience, types of data positions, and interview process. 226. Visualization of Hypothesis on Meteorological data In this blog, we are gonna perform the analysis on the Meteorological data, and prove the hypothesis based on visualization. 227. Employee Training: How to Make Data-Driven Business Decisions According to PwC research, highly data-driven organizations are three times more likely to witness considerable improvement in decision-making. Unfortunately, a whopping 62% of executives still rely more on experience and gut feelings than data to make business decisions. 228. 7 Ways to Beat Zoom Fatigue and Improve Your Virtual Meetings Zoom fatigue is plaguing productivity. Explore fun and data-driven ways to overcome the challenge and to add some personality to your next zoom call. 229. 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. Thank you for checking out the 229 most read stories about Data Analytics on HackerNoon. to find the most read stories about any technology. Visit the /Learn Repo