Sql For Data Analysis Advanced Techniques For Transforming Data Into Insights Github
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SQL for Data Analysis
With the explosion of computing power, thanks to analytic databases and cloud data warehouses, SQL has become an even more robust and flexible tool for the savvy analyst or data scientist. This practical book reveals hidden ways to get the most out of your SQL 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 waysâ??as well as how to combine SQL techniques to accomplish your goals faster, with more understandable code. If you work with SQL databases, this is a must-have reference. SQL for Data Analysis covers useful applications such as: Cohort analysis Text analysis Anomaly detection Time series analysis Experiment analysis Creating complex datasets for further exploration in statistical and visualization tools And more
SQL for Data Analysis
Author: Cathy Tanimura
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2021-09-09
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
SQL Cookbook
A guide to SQL covers such topics as retrieving records, metadata queries, working with strings, data arithmetic, date manipulation, reporting and warehousing, and hierarchical queries.