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SQL for Data Analytics

You're reading from  SQL for Data Analytics

Product type Book
Published in Aug 2019
Publisher Packt
ISBN-13 9781789807356
Pages 386 pages
Edition 1st Edition
Languages
Authors (3):
Upom Malik Upom Malik
Profile icon Upom Malik
Matt Goldwasser Matt Goldwasser
Profile icon Matt Goldwasser
Benjamin Johnston Benjamin Johnston
Profile icon Benjamin Johnston
View More author details

Table of Contents (11) Chapters

Preface 1. Understanding and Describing Data 2. The Basics of SQL for Analytics 3. SQL for Data Preparation 4. Aggregate Functions for Data Analysis 5. Window Functions for Data Analysis 6. Importing and Exporting Data 7. Analytics Using Complex Data Types 8. Performant SQL 9. Using SQL to Uncover the Truth – a Case Study Appendix

Best Practices for Importing and Exporting Data

At this point, we have seen several different methods for reading and writing data between our computer and our database. Each method has its own use case and purpose. Generally, there are going to be two key factors that should guide your decision-making process:

  • You should try to access the database with the same tool that you will use to analyze the data. As you add more steps to get your data from the database to your analytics tool, you increase the ways in which new errors can arise. When you can't access the database using the same tool that you will use to process the data, you should use psql to read and write CSV files to your database.
  • When writing data, you can save time by using the COPY or \copy commands.

Going Password-Less

In addition to everything mentioned so far, it is also a good idea to set up a .pgpass file. A .pgpass file specifies the parameters that you use to connect to your database...

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