SQL for Data Scientists
A Beginner's Guide for Building Datasets for Analysis
- English
- PDF
- Available on iOS & Android
About this book
Jump-start your career as a data scientistāl earn to develop datasets for exploration, analysis, and machine learning
SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that's dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls.
You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data.
This guide for data scientists differs from other instructional guides on the subject. It doesn't cover SQL broadly. Instead, you'll learn the subset of SQL skills that data analysts and data scientists use frequently. You'll also gain practical advice and direction on "how to think about constructing your dataset."
- Gain an understanding of relational database structure, query design, and SQL syntax
- Develop queries to construct datasets for use in applications like interactive reports and machine learning algorithms
- Review strategies and approaches so you can design analytical datasets
- Practice your techniques with the provided database and SQL code
In this book, author Renee Teate shares knowledge gained during a 15-year career working with data, in roles ranging from database developer to data analyst to data scientist. She guides you through SQL code and dataset design concepts from an industry practitioner's perspective, moving your data scientist career forward!
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Information
Table of contents
- Cover
- Title Page
- Copyright Page
- About theĀ Author
- About theĀ Technical Editor
- Acknowledgments
- Contents at a Glance
- Contents
- Introduction
- Chapter 1 Data Sources
- Chapter 2 The SELECT Statement
- Chapter 3 The WHERE Clause
- Chapter 4 CASE Statements
- Chapter 5 SQL JOINs
- Chapter 6 Aggregating Results forĀ Analysis
- Chapter 7 Window Functions andĀ Subqueries
- Chapter 8 Date andĀ Time Functions
- Chapter 9 Exploratory Data Analysis with SQL
- Chapter 10 Building SQL Datasets for Analytical Reporting
- Chapter 11 More Advanced Query Structures
- Chapter 12 Creating Machine Learning Datasets Using SQL
- Chapter 13 Analytical Dataset Development Examples
- Chapter 14 Storing andĀ Modifying Data
- Appendix Answers to Exercises
- Index
- EULA