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SQL for Data Analysis by Cathy Tanimura

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SQL for Data Analysis

Advanced Techniques for Transforming Data Into Insights

Cathy Tanimura

O'Reilly Media · Print & ebook · October 19, 2021

Reading lane: SQL & Databases

With the explosion of data, computing power, and cloud data warehouses, SQL has become an even more indispensable tool for the savvy analyst or data scientist.

At a Glance

Who It's For

For analysts or data scientists building SQL skillsFor SQL database users seeking analytical techniques

Book Details

Authors
Cathy Tanimura
Publisher
O'Reilly Media
Published
October 19, 2021
Format
Print & ebook
Theme
SQL & Databases · Data Mining
Reading lane
SQL & Databases

Affinity

Publisher Categories

  • Data Mining

  • Data Warehousing

  • SQL & Databases

  • Data Modeling

Show all 6 publisher categories
  • Math & Stats Software

  • Machine Learning

About This Book

With the explosion of data, computing power, and cloud data warehouses, SQL has become an even more indispensable tool for the savvy analyst or data scientist. This practical book reveals new and hidden ways to improve your SQL skills, solve problems, and make the most of SQL as part of your workflow. You'll learn how to use both common and exotic SQL functions such as joins, window functions, subqueries, and regular expressions in new, innovative ways--as well as how to com...

Read full description

With the explosion of data, computing power, and cloud data warehouses, SQL has become an even more indispensable tool for the savvy analyst or data scientist. This practical book reveals new and hidden ways to improve your SQL skills, solve problems, and make the most of SQL as part of your workflow. You'll learn how to use both common and exotic SQL functions such as joins, window functions, subqueries, and regular expressions in new, innovative ways--as well as how to combine SQL techniques to accomplish your goals faster, with understandable code. If you work with SQL databases, this is a must-have reference. - Learn the key steps for preparing your data for analysis - Perform time series analysis using SQL's date and time manipulations - Use cohort analysis to investigate how groups change over time - Use SQL's powerful functions and operators for text analysis - Detect outliers in your data and replace them with alternate values - Establish causality using experiment analysis, also known as A/B testing

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