While exposure to data has become more or less a daily ritual for the rank-and-file knowledge worker, true understanding—treated in this book as data literacy—resides in knowing what lies behind the data.

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While exposure to data has become more or less a daily ritual for the rank-and-file knowledge worker, true understanding—treated in this book as data literacy—resides in knowing what lies behind the data.



Everything, from the data’s source to the specific choice of input variables, algorithmic transformations, and visual representation all shape the accuracy, relevance, and value of the data and mark its journey from raw data to business insight.

It's important that you can grasp the terminology and basic concepts of data analytics just as much as you need to understand basic accounting and financial literacy to be a successful decision maker in the business world.

This book is ideal for anyone who is interested in making sense of data analytics without the assumption that you understand specific data science terminology or advanced programming languages.

Topics covered in this book:


Data Mining
Big Data
Machine Learning
Alternative Data
Data Management
Web Scraping
Regression Analysis
Clustering Analysis
Association Analysis
Data Visualization
Business Intelligence



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