book

Collect, Combine, and Transform Data Using Power Query in Excel and Power BI, First Edition

Name: Collect, Combine, and Transform Data Using Power Query in Excel and Power BI, First Edition
Author: Gil Raviv
ISBN: 9781509307982

by Gil Raviv

October 2018

Beginner to intermediate

432 pages

13h 20m

English

Microsoft Press

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Cover Page
Title Page
Copyright Page
Contents at a Glance
Contents
Figure Credits
Foreword
About the Author
Acknowledgments
Introduction
Who this book is forHow this book is organizedAbout the companion contentSystem requirementsHow to get support & provide feedback

Chapter 1 Introduction to Power Query
What Is Power Query?A Brief History of Power QueryWhere Can I Find Power Query?Main Components of Power QueryGet Data and ConnectorsThe Main Panes of the Power Query EditorExercise 1-1: A First Look at Power QuerySummary
Chapter 2 Basic Data Preparation Challenges
Extracting Meaning from Encoded ColumnsAdventureWorks ChallengeExercise 2-1: The Old Way: Using Excel FormulasExercise 2-2, Part 1: The New WayExercise 2-2, Part 2: Merging Lookup TablesExercise 2-2, Part 3: Fact and Lookup TablesUsing Column from ExamplesExercise 2-3, Part 1: Introducing Column from ExamplesPractical Use of Column from ExamplesExercise 2-3, Part 2: Converting Size to Buckets/RangesExtracting Information from Text ColumnsExercise 2-4: Extracting Hyperlinks from MessagesHandling DatesExercise 2-5: Handling Multiple Date FormatsExercise 2-6: Handling Dates with Two LocalesExtracting Date and Time ElementsPreparing the ModelExercise 2-7: Splitting Data into Lookup Tables and Fact TablesExercise 2-8: Splitting Delimiter-Separated Values into RowsSummary
Chapter 3 Combining Data from Multiple Sources
Appending a Few TablesAppending Two TablesExercise 3-1: Bikes and Accessories ExampleExercise 3-2, Part 1: Using Append Queries as NewExercise 3-2, Part 2: Query Dependencies and ReferencesAppending Three or More TablesExercise 3-2, Part 3: Bikes + Accessories + ComponentsExercise 3-2, Part 4: Bikes + Accessories + Components + ClothingAppending Tables on a Larger ScaleAppending Tables from a FolderExercise 3-3: Appending AdventureWorks Products from a FolderThoughts on Import from FolderAppending Worksheets from a WorkbookExercise 3-4: Appending Worksheets: The SolutionSummary
Chapter 4 Combining Mismatched Tables
The Problem of Mismatched TablesWhat Are Mismatched Tables?The Symptoms and Risks of Mismatched TablesExercise 4-1: Resolving Mismatched Column Names: The Reactive ApproachCombining Mismatched Tables from a FolderExercise 4-2, Part 1: Demonstrating the Missing Values SymptomExercise 4-2, Part 2: The Same-Order Assumption and the Header Generalization SolutionExercise 4-3: Simple Normalization Using Table.TransformColumnNamesThe Conversion TableExercise 4-4: The Transpose Techniques Using a Conversion TableExercise 4-5: Unpivot, Merge, and Pivot BackExercise 4-6: Transposing Column Names OnlyExercise 4-7: Using M to Normalize Column NamesSummary
Chapter 5 Preserving Context
Preserving Context in File Names and WorksheetsExercise 5-1, Part 1: Custom Column TechniqueExercise 5-1, Part 2: Handling Context from File Names and Worksheet NamesPre-Append Preservation of TitlesExercise 5-2: Preserving Titles Using Drill DownExercise 5-3: Preserving Titles from a FolderPost-Append Context Preservation of TitlesExercise 5-4: Preserving Titles from Worksheets in the same WorkbookUsing Context CuesExercise 5-5: Using an Index Column as a CueExercise 5-6: Identifying Context by Cell ProximitySummary
Chapter 6 Unpivoting Tables
Identifying Badly Designed TablesIntroduction to UnpivotExercise 6-1: Using Unpivot Columns and Unpivot Other ColumnsExercise 6-2: Unpivoting Only Selected ColumnsHandling TotalsExercise 6-3: Unpivoting Grand TotalsUnpivoting 2×2 Levels of HierarchyExercise 6-4: Unpivoting 2×2 Levels of Hierarchy with DatesExercise 6-5: Unpivoting 2×2 Levels of HierarchyHandling Subtotals in Unpivoted DataExercise 6-6: Handling SubtotalsSummary
Chapter 7 Advanced Unpivoting and Pivoting of Tables
Unpivoting Tables with Multiple Levels of HierarchyThe Virtual PivotTable, Row Fields, and Column FieldsExercise 7-1: Unpivoting the AdventureWorks N×M Levels of HierarchyGeneralizing the Unpivot SequenceExercise 7-2: Starting at the EndExercise 7-3: Creating FnUnpivotSummarizedTableThe Pivot Column TransformationExercise 7-4: Reversing an Incorrectly Unpivoted TableExercise 7-5: Pivoting Tables of Multiline RecordsSummary
Chapter 8 Addressing Collaboration Challenges
Local Files, Parameters, and TemplatesAccessing Local Files—IncorrectlyExercise 8-1: Using a Parameter for a Path NameExercise 8-2: Creating a Template in Power BIExercise 8-3: Using Parameters in ExcelWorking with Shared Files and FoldersImporting Data from Files on OneDrive for Business or SharePointExercise 8-4: Migrating Your Queries to Connect to OneDrive for Business or SharePointExercise 8-5: From Local to SharePoint FoldersSecurity ConsiderationsRemoving All Queries Using the Document Inspector in ExcelSummary
Chapter 9 Introduction to the Power Query M Formula Language
Learning MLearning Maturity StagesOnline ResourcesOffline ResourcesExercise 9-1: Using #shared to Explore Built-in FunctionsM Building BlocksExercise 9-2: Hello WorldThe let ExpressionMerging Expressions from Multiple Queries and Scope ConsiderationsTypes, Operators, and Built-in Functions in MBasic M TypesThe Number TypeThe Time TypeThe Date TypeThe Duration TypeThe Text TypeThe Null TypeThe Logical TypeComplex TypesThe List TypeThe Record TypeThe Table TypeConditions and If Expressionsif-then-elseAn if Expression Inside a let ExpressionCustom FunctionsInvoking FunctionsThe each ExpressionAdvanced TopicsError HandlingLazy and Eager EvaluationsLoopsRecursionList.GenerateList.AccumulateSummary
Chapter 10 From Pitfalls to Robust Queries
The Causes and Effects of the PitfallsAwarenessBest PracticesM ModificationsPitfall 1: Ignoring the Formula BarExercise 10-1: Using the Formula Bar to Detect Static References to Column NamesPitfall 2: Changed TypesPitfall 3: Dangerous FilteringExercise 10-2, Part 1: Filtering Out Black ProductsThe Logic Behind the Filtering ConditionExercise 10-2, Part 2: Searching Values in the Filter PanePitfall 4: Reordering ColumnsExercise 10-3, Part 1: Reordering a Subset of ColumnsExercise 10-3, Part 2: The Custom Function FnReorderSubsetOfColumnsPitfall 5: Removing and Selecting ColumnsExercise 10-4: Handling the Random Columns in the Wide World Importers TablePitfall 6: Renaming ColumnsExercise 10-5: Renaming the Random Columns in the Wide World Importers TablePitfall 7: Splitting a Column into ColumnsExercise 10-6: Making an Incorrect SplitPitfall 8: Merging ColumnsMore Pitfalls and Techniques for Robust QueriesSummary
Chapter 11 Basic Text Analytics
Searching for Keywords in Textual ColumnsExercise 11-1: Basic Detection of KeywordsUsing a Cartesian Product to Detect KeywordsExercise 11-2: Implementing a Cartesian ProductExercise 11-3: Detecting Keywords by Using a Custom FunctionWhich Method to Use: Static Search, Cartesian Product, or Custom Function?Word SplitsExercise 11-4: Naïve Splitting of WordsExercise 11-5: Filtering Out Stop WordsExercise 11-6: Searching for Keywords by Using Split WordsExercise 11-7: Creating Word Clouds in Power BISummary
Chapter 12 Advanced Text Analytics: Extracting Meaning
Microsoft Azure Cognitive ServicesAPI Keys and Resources Deployment on AzurePros and Cons of Cognitive Services via Power QueryText TranslationThe Translator Text API ReferenceExercise 12-1: Simple TranslationExercise 12-2: Translating Multiple MessagesSentiment AnalysisWhat Is the Sentiment Analysis API Call?Exercise 12-3: Implementing the FnGetSentiment Sentiment Analysis Custom FunctionExercise 12-4: Running Sentiment Analysis on Large DatasetsExtracting Key PhrasesExercise 12-5: Converting Sentiment Logic to Key PhrasesMulti-Language SupportReplacing the Language CodeDynamic Detection of LanguagesExercise 12-6: Converting Sentiment Logic to Language DetectionSummary
Chapter 13 Social Network Analytics
Getting Started with the Facebook ConnectorExercise 13-1: Finding the Pages You LikedAnalyzing Your FriendsExercise 13-2: Finding Your Power BI Friends and Their FriendsExercise 13-3: Find the Pages Your Friends LikedAnalyzing Facebook PagesExercise 13-4: Extracting Posts and Comments from Facebook Pages—The Basic WayShort Detour: Filtering Results by TimeExercise 13-5: Analyzing User Engagement by Counting Comments and SharesExercise 13-6: Comparing Multiple PagesSummary
Chapter 14 Final Project: Combining It All Together
Exercise 14-1: Saving the Day at Wide World ImportersCluesPart 1: Starting the SolutionPart 2: Invoking the Unpivot FunctionPart 3: The Pivot Sequence on 2018 RevenuesPart 4: Combining the 2018 and 2015–2017 RevenuesExercise 14-2: Comparing Tables and Tracking the HackerCluesExercise 14-2: The SolutionDetecting the Hacker’s Footprints in the Compromised TableSummary
Index
Code Snippets

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COLLECT, COMBINE, AND TRANSFORM DATA USING POWER QUERY IN EXCEL AND POWER BI

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