Data Modeling with Microsoft Excel (eBook)

Model and analyze data using Power Pivot, DAX, and Cube functions
eBook Download: EPUB
2023
316 Seiten
Packt Publishing (Verlag)
978-1-80323-692-6 (ISBN)

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Data Modeling with Microsoft Excel - Bernard Obeng Boateng
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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.


Save time analyzing volumes of data using a structured method to extract, model, and create insights from your dataKey FeaturesAcquire expertise in using Excel's Data Model and Power Pivot to connect and analyze multiple sources of dataCreate key performance indicators for decision making using DAX and Cube functionsApply your knowledge of Data Model to build an interactive dashboard that delivers key insights to your usersPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMicrosoft 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.What you will learnImplement the concept of data modeling within and beyond ExcelGet, transform, model, aggregate, and visualize data with Power QueryUnderstand best practices for data structuring in MS ExcelBuild powerful measures using DAX from the Data ModelGenerate flexible calculations using Cube functionsDesign engaging dashboards for your usersWho this book is forThis book is for Excel users looking for hands-on and effective methods to manage and analyze large volumes of data within Microsoft Excel using Power Pivot. Whether you re new or already familiar with Excel s data analytics tools, this book will give you further insights on how you can apply Power Pivot, Data Model, DAX measures, and Cube functions to save time on routine data management tasks. An understanding of Excel s features like tables, PivotTable, and some basic aggregating functions will be helpful but not necessary to make the most of this book.]]>
Erscheint lt. Verlag 30.11.2023
Vorwort Michael Olafusi
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Datenbanken
Mathematik / Informatik Informatik Web / Internet
ISBN-10 1-80323-692-2 / 1803236922
ISBN-13 978-1-80323-692-6 / 9781803236926
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