how to lie with statistics
Misleading Statistics: How to Be Safe From Statistical Manipulation?

Misleading graphs are everywhere. This book will teach you how statistics can be tricky with examples.

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Disadvantages of Artificial Neural Networks And Workarounds

Artificial Neural Networks (ANN) has several disadvantages. Yet, we have techniques to overcome them and use it successfully.

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Data Teams Are Becoming Less Centralized, and That's Wonderful

Businesses should celebrate modern shifts in the AI/ML technology landscape.

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The Difference Between Data Warehouses, Data Lakes, and Data Lakehouses.

Data warehouse vs. data lake vs. data lakehouse. Why should you choose data lake over data warehouse? And how building a data lakehouse can benefit more?

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Data Dilemma: Too Much Data Can Be a Problem for Businesses Rather Than Helpful

There are a few things to keep in mind when dealing with data to avoid common data dilemmas and get the most out it.

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Four Simple Criteria for Choosing Your Next Advanced Analytics Project

There are several questions you can ask yourself when deciding which analytics project to take on next. Four criteria have proven to be the most helpful in making this decision.

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In the 8 Key MLOps Roles, Where Do You Fit In?

Large-scale data science teams can have several distinct roles & responsibilities to manage machine learning operations.

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Citizen data scientists transform the way organizations work - Photo by Keira Burton from Pexels.
Welcome to the Age of Citizen Data Scientists

Data science has been democratized for the most part. AI is now mainstream! Here's how you can become a citizen data scientist.

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The Mistake Companies Make When Creating Their Data Science Foundation
The #1 Mistake Companies Make When Creating Their Data Science Foundation

85 % of data science projects fail because companies are obsessed with complex models such as deep learning. Simple models often can solve their problems.

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How to Improve Data Quality With Data Quality Assessment?

Here are the six data quality dimensions and how to use continuous data quality assessments in your business.

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