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

Using Power Query, you can import, reshape, and cleanse any data from a simple interface, so you can mine that data for all of its hidden insights. Power Query is embedded in Excel, Power BI, and other Microsoft products, and leading Power Query expert Gil Raviv will help you make the most of it. Discover how to eliminate time-consuming manual data preparation, solve common problems, avoid pitfalls, and more. Then, walk through several complete analytics challenges, and integrate all your skills in a realistic chapter-length final project. By the time you're finished, you'll be ready to wrangle any data-and transform it into actionable knowledge.

Prepare and analyze your data the easy way, with Power Query

· Quickly prepare data for analysis with Power Query in Excel (also known as Get & Transform) and in Power BI

· Solve common data preparation problems with a few mouse clicks and simple formula edits

· Combine data from multiple sources, multiple queries, and mismatched tables

· Master basic and advanced techniques for unpivoting tables

· Customize transformations and build flexible data mashups with the M formula language

· Address collaboration challenges with Power Query

· Gain crucial insights into text feeds

· Streamline complex social network analytics so you can do it yourself

For all information workers, analysts, and any Excel user who wants to solve their own business intelligence problems.

Autorentext

Gil Raviv is a Microsoft MVP and a Power BI blogger at https://DataChant.com. As a Senior Program Manager on the Microsoft Excel Product team, Gil led the design and integration of Power Query as the next-generation Get Data and data-wrangling technology in Excel 2016, and he has been a devoted M practitioner ever since.

With 20 years of software development experience, and four U.S. patents in the fi elds of social networks, cyber security, and analytics, Gil has held a variety of innovative roles in cyber security and data analytics, and he has delivered a wide range of software products, from advanced threat detection enterprise systems to protection of kids on Facebook.

In his blog, DataChant.com, Gil has been chanting about Power BI and Power Query since he moved to his new home in the Chicago area in early 2016. As a Group Manager in Avanade's Analytics Practice, Gil is helping Fortune 500 clients create modern self-service analytics capability and solutions by leveraging Power BI and Azure.

You can contact Gil at gilra@datachant.com.

Inhalt

Introduction

Chapter 1 Introduction to Power Query

What Is Power Query?

A Brief History of Power Query

Where Can I Find Power Query?

Main Components of Power Query

Get Data and Connectors

The Main Panes of the Power Query Editor

Exercise 1-1: A First Look at Power Query

Summary

Chapter 2 Basic Data Preparation Challenges

Extracting Meaning from Encoded Columns

AdventureWorks Challenge

Exercise 2-1: The Old Way: Using Excel Formulas

Exercise 2-2, Part 1: The New Way

Exercise 2-2, Part 2: Merging Lookup Tables

Exercise 2-2, Part 3: Fact and Lookup Tables

Using Column from Examples

Exercise 2-3, Part 1: Introducing Column from Examples

Practical Use of Column from Examples

Exercise 2-3, Part 2: Converting Size to Buckets/Ranges

Extracting Information from Text Columns

Exercise 2-4: Extracting Hyperlinks from Messages

Handling Dates

Exercise 2-5: Handling Multiple Date Formats

Exercise 2-6: Handling Dates with Two Locales

Extracting Date and Time Elements

Preparing the Model

Exercise 2-7: Splitting Data into Lookup Tables and Fact Tables

Exercise 2-8: Splitting Delimiter-Separated Values into Rows

Summary

Chapter 3 Combining Data from Multiple Sources

Appending a Few Tables

Appending Two Tables

Exercise 3-1: Bikes and Accessories Example

Exercise 3-2, Part 1: Using Append Queries as New

Exercise 3-2, Part 2: Query Dependencies and References

Appending Three or More Tables

Exercise 3-2, Part 3: Bikes + Accessories + Components

Exercise 3-2, Part 4: Bikes + Accessories + Components + Clothing

Appending Tables on a Larger Scale

Appending Tables from a Folder

Exercise 3-3: Appending AdventureWorks Products from a Folder

Thoughts on Import from Folder

Appending Worksheets from a Workbook

Exercise 3-4: Appending Worksheets: The Solution

Summary

Chapter 4 Combining Mismatched Tables

The Problem of Mismatched Tables

What Are Mismatched Tables?

The Symptoms and Risks of Mismatched Tables

Exercise 4-1: Resolving Mismatched Column Names: The Reactive Approach

Combining Mismatched Tables from a Folder

Exercise 4-2, Part 1: Demonstrating the Missing Values Symptom

Exercise 4-2, Part 2: The Same-Order Assumption and the Header Generalization Solution

Exercise 4-3: Simple Normalization Using Table.TransformColumnNames

The Conversion Table

Exercise 4-4: The Transpose Techniques Using a Conversion Table

Exercise 4-5: Unpivot, Merge, and Pivot Back

Exercise 4-6: Transposing Column Names Only

Exercise 4-7: Using M to Normalize Column Names

Summary

Chapter 5 Preserving Context

Preserving Context in File Names and Worksheets

Exercise 5-1, Part 1: Custom Column Technique

Exercise 5-1, Part 2: Handling Context from File Names and Worksheet Names

Pre-Append Preservation of Titles

Exercise 5-2: Preserving Titles Using Drill Down

Exercise 5-3: Preserving Titles from a Folder

Post-Append Context Preservation of Titles

Exercise 5-4: Preserving Titles from Worksheets in the same Workbook

Using Context Cues

Exercise 5-5: Using an Index Column as a Cue

Exercise 5-6: Identifying Context by Cell Proximity

Summary

Chapter 6 Unpivoting Tables

Identifying Badly Designed Tables

Introduction to Unpivot

Exercise 6-1: Using Unpivot Columns and Unpivot Other Columns

Exercise 6-2: Unpivoting Only Selected Columns

Handling Totals

Exercise 6-3: Unpivoting Grand Totals

Unpivoting 2Levels of Hierarchy

Exercise 6-4: Unpivoting 2Levels of Hierarchy with Dates

Exercise 6-5: Unpivoting 2Levels of Hierarchy

Handling Subtotals in Unpivoted Data

Exercise 6-6: Handling Subtotals

Summary

Chapter 7 Advanced Unpivoting and Pivoting of Tables

Unpivoting Tables with Multiple Levels of Hierarchy

The Virtual PivotTable, Row Fields, and Column Fields

Exercise 7-1: Unpivoting the AdventureWorks N Levels of Hierarchy

Generalizing the Unpivot Sequence

Exercise 7-2: Starting at the End

Exercise 7-3: Creating FnUnpivotSummarizedTable

The Pivot Column Transformation

Exercise 7-4: Reversing an Incorrectly Unpivoted Table

Exercise 7-5: Pivoting Tables of Multiline Records

Summary

Chapter 8 Addressing Collaboration Challenges

Local Files, Parameters, and Templates

Accessing Local Files-Incorrectly

Exercise 8-1: Using a Parameter for a Path Name

Exercise 8-2: Creating a Template in Power BI

Exercise 8-3: Using Parameters in Excel

Working with Shared Files and Folders

Importing Data from Files on OneDrive for Business or SharePoint

Exercise 8-4: Migrating Your Queries to Connect to OneDrive for Business or SharePoint

Exercise 8-5: From Local to SharePoint Folders

Security Considerations

Removing All Queries Using the Document Inspector in Excel

Summary

Chapter 9 Introduction to the Power Query M Formula Language

Learning M

Learning Maturity Stages

Online Resources

Offline Resources

Exercise 9-1: Using #shared to Explore Built-in Functions

M Building Blocks

Exercise 9-2: Hello World

The let Expression

Merging Expressions from Multiple Queries and Scope Considerations

Types, Operators, and Built-in Functions in M

Basic M Types

The Number Type

The Time Type

The Date Type

The Duration Type

The Text Type

The Null Type

The Logical Type

Complex Types

The Li…