Data analysis using SQL and Excel / Gordon S. Linoff.

Format:

Book

Author/Creator:

Linoff, Gordon S., author.

Series:

THEi Wiley ebooks.

THEi Wiley ebooks

Language:

English

Subjects (All):

SQL (Computer program language).

Querying (Computer science).

Data mining.

Microsoft Excel (Computer file).

Physical Description:

1 online resource (795 p.)

Edition:

Second edition.

Place of Publication:

Indianapolis, Indiana : Wiley, 2016.

Language Note:

English

System Details:

Access using campus network via VPN at home (THEi Users Only).

Summary:

A practical guide to data mining using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis-SQL and Excel-to perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this book shows you how to extract useful business information from relational databases. You'll learn the fundamental techniques before moving into the "where" and "why" of each analysis, and then learn how to design and perform these analyses using SQL and Excel. Examples include SQL and Excel code, and the appendix shows how non-standard constructs are implemented in other major databases, including Oracle and IBM DB2/UDB. The companion website includes datasets and Excel spreadsheets, and the book provides hints, warnings, and technical asides to help you every step of the way. Data Analysis Using SQL and Excel, 2nd Edition shows you how to perform a wide range of sophisticated analyses using these simple tools, sparing you the significant expense of proprietary data mining tools like SAS. * Understand core analytic techniques that work with SQL and Excel * Ensure your analytic approach gets you the results you need * Design and perform your analysis using SQL and Excel Data Analysis Using SQL and Excel, 2nd Edition shows you how to best use the tools you already know to achieve expert results.

Contents:

Data Analysis Using SQL and Excel®; About the Author; Credits; Acknowledgments; Contents at a Glance; Contents; Foreword; Introduction; Chapter 1 A Data Miner Looks at SQL; Databases, SQL, and Big Data; What Is Big Data?; Relational Databases; Hadoop and Hive; NoSQL and Other Types of Databases; SQL; Picturing the Structure of the Data; What Is a Data Model?; What Is a Table?; Allowing NULL Values; Column Types; What Is an Entity-Relationship Diagram?; The Zip Code Tables; Subscription Dataset; Purchases Dataset; Tips on Naming Things; Picturing Data Analysis Using Dataflows

What Is a Dataflow? READ: Reading a Database Table; OUTPUT: Outputting a Table (or Chart); SELECT: Selecting Various Columns in the Table; FILTER: Filtering Rows Based on a Condition; APPEND: Appending New Calculated Columns; UNION: Combining Multiple Datasets into One; AGGREGATE: Aggregating Values; LOOKUP: Looking Up Values in One Table in Another; CROSS JOIN: Generating the Cartesian Product of Two Tables; JOIN: Combining Two Tables Using a Key Column; SORT: Ordering the Results of a Dataset; Dataflows, SQL, and Relational Algebra; SQL Queries; What to Do, Not How to Do It

The SELECT Statement A Basic SQL Query; A Basic Summary SQL Query; What It Means to Join Tables; Cross-Joins: The Most General Joins; Lookup: A Useful Join; Equijoins; Nonequijoins; Outer Joins; Other Important Capabilities in SQL; UNION ALL; CASE; IN; Window Functions; Subqueries and Common Table Expressions Are Our Friends; Subqueries for Naming Variables; Subqueries for Handling Summaries; Subqueries and IN; Rewriting the "IN" as a JOIN; Correlated Subqueries; NOT IN Operator; EXISTS and NOT EXISTS Operators; Subqueries for UNION ALL; Lessons Learned

Chapter 2 What's in a Table? Getting Started with Data Exploration What Is Data Exploration?; Excel for Charting; A Basic Chart: Column Charts; Inserting the Data; Creating the Column Chart; Formatting the Column Chart; Bar Charts in Cells; Character-Based Bar Charts; Conditional Formatting-Based Bar Charts; Useful Variations on the Column Chart; A New Query; Side-by-Side Columns; Stacked Columns; Stacked and Normalized Columns; Number of Orders and Revenue; Other Types of Charts; Line Charts; Area Charts; X-Y Charts (Scatter Plots); Sparklines; What Values Are in the Columns?; Histograms

Histograms of Counts Cumulative Histograms of Counts; Histograms (Frequencies) for Numeric Values; Ranges Based on the Number of Digits, Using Numeric Techniques; Ranges Based on the Number of Digits, Using String Techniques; More Refined Ranges: First Digit Plus Number of Digits; Breaking Numeric Values into Equal-Sized Groups; More Values to Explore-Min, Max, and Mode; Minimum and Maximum Values; The Most Common Value (Mode); Calculating Mode Using Basic SQL; Calculating Mode Using Window Functions; Exploring String Values; Histogram of Length; Strings Starting or Ending with Spaces

Handling Upper- and Lowercase

Notes:

Includes index.

Description based on online resource; title from PDF title page (ebrary, viewed December 28, 2015).

ISBN:

9781119021445

1119021448

9781119183419

1119183413

9781119021452

1119021456

OCLC:

931864545