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SQL for Data Analysis: Advanced - Paperback, by Tanimura Cathy - Very Good
US $25,61
CircaEUR 21,83
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Gratis USPS Media MailTM.
Oggetto che si trova a: Philadelphia, Pennsylvania, Stati Uniti
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Consegna prevista tra il lun 6 ott e il sab 11 ott a 94104
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Numero oggetto eBay:126973083043
Specifiche dell'oggetto
- Condizione
- Book Title
- SQL for Data Analysis: Advanced Techniques for Transforming Data
- ISBN
- 9781492088783
Informazioni su questo prodotto
Product Identifiers
Publisher
O'reilly Media, Incorporated
ISBN-10
1492088781
ISBN-13
9781492088783
eBay Product ID (ePID)
17050379040
Product Key Features
Number of Pages
357 Pages
Publication Name
Sql for Data Analysis : Advanced Techniques for Transforming Data Into Insights
Language
English
Publication Year
2021
Subject
Data Modeling & Design, General, Programming Languages / Sql, Databases / Data Mining
Type
Textbook
Subject Area
Mathematics, Computers
Format
Trade Paperback
Dimensions
Item Height
1.4 in
Item Weight
21.4 Oz
Item Length
9.2 in
Item Width
7 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2022-300024
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
005.75/65
Synopsis
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
LC Classification Number
QA76.73.S67
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