Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Data Modeling with Microsoft Excel

You're reading from   Data Modeling with Microsoft Excel Model and analyze data using Power Pivot, DAX, and Cube functions

Arrow left icon
Product type Paperback
Published in Nov 2023
Publisher Packt
ISBN-13 9781803240282
Length 316 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Bernard Obeng Boateng Bernard Obeng Boateng
Author Profile Icon Bernard Obeng Boateng
Bernard Obeng Boateng
Arrow right icon
View More author details
Toc

Table of Contents (16) Chapters Close

Preface 1. Part 1: Overview and Introduction to Data Modeling in Microsoft Excel
2. Chapter 1: Getting Started with Data Modeling – Overview and Importance FREE CHAPTER 3. Chapter 2: Data Structuring for Data Models – What’s the best way to layout your data? 4. Chapter 3: Preparing Your Data for the Data Model – Cleaning and Transforming Your Data Using Power Query 5. Chapter 4: Data Modeling with Power Pivot – Understanding How to Combine and Analyze Multiple Tables Using the Data Model 6. Part 2: Creating Insightful Calculations from your Data Model using DAX and Cube Functions
7. Chapter 5: Creating DAX Calculations from Your Data Model – Introduction to Measures and Calculated Columns 8. Chapter 6: Creating Cube Functions from Your Data Model – a Flexible Alternative to Calculations in Your Data Model 9. Part 3: Putting it all together with a Dashboard
10. Chapter 7: Communicating Insights from Your Data Model Using Dashboards – Overview and Uses 11. Chapter 8: Visualization Elements for Your Dashboard – Slicers, PivotCharts, Conditional Formatting, and Shapes 12. Chapter 9: Choosing the Right Design Themes – Less Is More with Colors 13. Chapter 10: Publication and Deployment – Sharing with Report Users 14. Index 15. Other Books You May Enjoy

Add Column or Transform?

Before we bring in our sales data, let us go back to our customer data query for one more transformation. This example will help us understand the key differences between performing a task with the Transform and Add Column tabs. In the customers query, we have the names of our customers in two columns. We want to merge these names into one column. Let’s do this from the Add Column tab to see the results we will get.

To do this, follow these steps:

  1. Go to the Add Column tab.
  2. Select the two columns First Name and Last Name.
  3. Click on Merge Columns in the Add Column tab.
Figure 3.18 – Merging columns under the Add Column tab

Figure 3.18 – Merging columns under the Add Column tab

  1. This brings up a dialog box that requires a separator and a name for our new column.
Figure 3.19 – Selecting a separator in Merge Columns

Figure 3.19 – Selecting a separator in Merge Columns

You can select Space for the separator and Full Name for the new column name.

When you click...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime