Lillian Pierson's Blog, page 11

What is Data Modeling – Data Modeling vs Data Analysis 101

The disciplines and subdisciplines of data are complex and often overlaid. Data analysis, engineering, and science are foundational concepts, while data modeling refers to the process of mapping data at conceptual, logical, and physical levels.  Data modeling overlaps with data science, engineering, and analysis, but its angle is probably more towards the engineering side of […]

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How to find new NFT Projects: 6 metrics you MUST evaluate

Are you interested on how to find new NFT projects? NFTs are sweeping the Internet, but what makes new NFT projects a smart investment? Much of the hype surrounding NFTs (or non-fungible tokens) is focused on the extreme prices at which some rare assets are sold. With non-stop buzz about one NFT trend or another, […]

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Naysayers of Decentralized Web 3.0: What They’re Saying and Why?

If you’re like most data professionals, you are still scratching your head about the decentralized web, or “Web 3.0”. You are also thinking about whether it’s really here to stay. And while the buzz about decentralized web has been heating up lately, it has included quite a bit of criticism. These criticisms are from some […]

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Web 3 and Data Science: A Quick Start Guide

If you’re curious about Web 3 and data science; And how the advancement of Web 3 can potentially impact and elevate your career in data science, this post is for you. Web 3, or Web 3, is the latest buzzword to take over the internet. The topic has drawn the attention of Twitter, GameStop and […]

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NFT Hype: All Hype or Mega Market Opportunity For Data Professionals?

If your busy schedule as a data professional has you a little behind the eight-ball with respect to what’s happening  in the NFT scene – and how that’s likely to affect the future of your data career – then this article is for you. NFTs have risen to the forefront of Internet trends over the […]

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Storing Data in the Public Cloud: What You Should Know

A public cloud is a platform that relies on the standard cloud computing model, making resources accessible to users remotely. Such resources include applications, virtual machines, or storage. Cloud costs are typically operating expenses (OpEx) and not capital expenses (CapEx) – most cloud services are offered on a pay per use basis. The public cloud […]

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4 steps to selecting an optimal analytics tool

If you’re responsible for selecting an analytics tool to help your data project or product achieve a strong ROI, then this article is for you. That’s because I’m about to share with you a battle-tested 4-step process for planning a data-project and exactly what you need to do to select the optimal analytics tool for […]

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Top 4 Reasons NOT to Learn Machine Learning

If you’re considering learning Machine Learning (ML), read this first. With all the ML hype out there these days, all you ever hear about is how machine learning  and data scientists are so great. No one ever talks about the drawbacks of becoming a data scientist. So, in today’s update I’m going to give you […]

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5 Ways to use R Programming for Data Science

The use of data science and statistics to solve problems is ever increasing. For this reason, R is a valuable language to learn, especially for those interested in analyzing data and solving real-world problems. Altogether, what is R programming? R is a universal programming language with various uses, particularly in data science. It offers statistical […]

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What Is Data Content? How to Use It to Grow a Data Business

Even if you don’t know it by name, you’ve probably seen examples of content marketing before. It does a lot of the heavy lifting in public relations and search engine optimization. Choosing the right kind of content to offer or sell is vital. When data, digital design or information services are your primary products, you […]

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