SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis Paperback - 2021
by Teate, Renee M. P
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- Paperback
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Details
- Title SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis
- Author Teate, Renee M. P
- Binding Paperback
- Condition Used - Very good
- Pages 288
- Volumes 1
- Language ENG
- Publisher Wiley
- Publication date 2021-09-15
- Features Index
- Bookseller's Inventory # GOR013738204
- ISBN 9781119669364 / 1119669367
- Weight 1.05 lbs (0.48 kg)
- Dimensions 9.1 x 7.3 x 0.6 in (23.11 x 18.54 x 1.52 cm)
- Category Computers - Languages / Programming
- Library of Congress subjects SQL (Computer program language), Instructional and educational works
- Library of Congress Catalogue Number 2021941400
- Dewey Decimal Code 005.756
- Quantity available 1
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From the publisher
From the rear cover
Jumpstart your data science career with crucial SQL skills
Today, many organizations expect their data scientists to be able to design and generate their own datasets by extracting and combining raw data from the company's data warehouses without the assistance of data engineers.
In SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis, experienced data scientist and database developer Rene M. P. Teate delivers a singular guide to the SQL skills and techniques every data scientist should know. You'll discover how to approach query design and develop SQL code to construct datasets for exploration, analysis, and data science.
SQL for Data Scientists shows you how to create datasets for use in applications like interactive reports and dashboards, as well as in machine learning algorithms. You'll skip right to the subset of SQL skills that data scientists and analysts use most frequently, and receive expert advice on extracting insights from data while avoiding common pitfalls.
- Understand fundamental SQL syntax and design effective SQL queries
- Conduct Exploratory Data Analysis with SQL
- Construct, filter, and sort your own datasets from pre-existing databases
- Use SQL JOINs to combine data from multiple database tables
- Design datasets for analytical reports and machine learning applications
- Apply more advanced SQL techniques such as Window Functions and Common Table Expressions
- Create database tables and views to store and retrieve the results of your queries
