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Data Modeling with Microsoft Excel

Data Modeling with Microsoft Excel

By : Bernard Obeng Boateng
4.6 (8)
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Data Modeling with Microsoft Excel

Data Modeling with Microsoft Excel

4.6 (8)
By: Bernard Obeng Boateng

Overview of this book

Microsoft Excel's BI solutions have evolved, offering users more flexibility and control over analyzing data directly in Excel. Features like PivotTables, Data Model, Power Query, and Power Pivot empower Excel users to efficiently get, transform, model, aggregate, and visualize data. Data Modeling with Microsoft Excel offers a practical way to demystify the use and application of these tools using real-world examples and simple illustrations. This book will introduce you to the world of data modeling in Excel, as well as definitions and best practices in data structuring for both normalized and denormalized data. The next set of chapters will take you through the useful features of Data Model and Power Pivot, helping you get to grips with the types of schemas (snowflake and star) and create relationships within multiple tables. You’ll also understand how to create powerful and flexible measures using DAX and Cube functions. By the end of this book, you’ll be able to apply the acquired knowledge in real-world scenarios and build an interactive dashboard that will help you make important decisions. Note: To access the supplemental material, subscribers should purchase a print copy of the book. The ebook can be accessed through the QR code or link provided inside the Print book. Proof of purchase is mandatory to access the ebook.
Table of Contents (16 chapters)
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1
Part 1: Overview and Introduction to Data Modeling in Microsoft Excel
6
Part 2: Creating Insightful Calculations from your Data Model using DAX and Cube Functions
9
Part 3: Putting it all together with a Dashboard

Summary

The objective of this chapter was to help you understand the concept of data modeling. We have covered the key advantages of using a data model in analyzing large and complex datasets. The chapter introduced you to tables, PivotTables, and Power Pivot and how the data model you create in Power Pivot helps you analyze data from multiple table sources. To help you put this in context, we looked at two practical use cases of a data model for an accountant and a salesperson. This should help bring the concept home and help you apply it to any dataset you analyze at work.

After reading this chapter, you are now also able to identify the key components of Power Pivot, the main authoring tool for data modeling in Microsoft Excel and Power BI. In this chapter, we also covered some best practices with a data model to help you improve the performance of Power Pivot.

In the next chapter, we will see best practices for laying out data. The chapter will help you further improve the performance of your Power Pivot calculations for large datasets.

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