04790nam 2200697 450 991013717790332120230731114256.01-119-02144-81-119-18341-31-119-02145-6(CKB)3710000000526798(EBL)4187166(SSID)ssj0001636516(PQKBManifestationID)16387376(PQKBTitleCode)TC0001636516(PQKBWorkID)14950804(PQKB)10707684(Au-PeEL)EBL4187166(CaPaEBR)ebr11128093(CaONFJC)MIL879752(OCoLC)932049818(CaSebORM)9781119021438(MiAaPQ)EBC4187166(PPN)194575209(EXLCZ)99371000000052679820151228h20162016 uy 0engurcnu||||||||txtccrData analysis using SQL and Excel /Gordon S. LinoffSecond edition.Indianapolis, Indiana :Wiley,2016.©20161 online resource (795 p.)THEi Wiley ebooksIncludes index.1-119-02143-X 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 DataflowsWhat 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 ItThe 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 LearnedChapter 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?; HistogramsHistograms 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 SpacesHandling Upper- and LowercaseTHEi Wiley ebooks.SQL (Computer program language)Querying (Computer science)Data miningSQL (Computer program language)Querying (Computer science)Data mining.005.756Linoff Gordon S.145033MiAaPQMiAaPQMiAaPQBOOK9910137177903321Data analysis using SQL and Excel1907340UNINA