Data Modeling with Microsoft Excel: Model and analyze data using Power Pivot, DAX, and Cube functions

· Packt Publishing Ltd
Ebook
316
Pages

About this ebook

Save time analyzing volumes of data using a structured method to extract, model, and create insights from your dataKey Features
  • Acquire expertise in using Excel’s Data Model and Power Pivot to connect and analyze multiple sources of data
  • Create key performance indicators for decision making using DAX and Cube functions
  • Apply your knowledge of Data Model to build an interactive dashboard that delivers key insights to your users
  • Purchase of the print or Kindle book includes a free PDF eBook
Book 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 learn
  • Implement the concept of data modeling within and beyond Excel
  • Get, transform, model, aggregate, and visualize data with Power Query
  • Understand best practices for data structuring in MS Excel
  • Build powerful measures using DAX from the Data Model
  • Generate flexible calculations using Cube functions
  • Design engaging dashboards for your users
Who this book is for

This 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.

About the author

Bernard Obeng Boateng is a Microsoft Excel MVP, Microsoft Certified Trainer, with over 10 years work experience in Banking, Insurance and Business Development. He is founder of Finex Skills Hub an approved Training Provider of the Financial Modeling Institute, Canada. Finex Skills Hub runs the Finex Project in Ghana, a pro bono student training outreach program for students in Data Analytics and Financial Modeling. Bernard also provides consultancy services for SMEs (start-ups and existing) in Financial Management, Business Planning and Research. He has an active audience online with about 17,000 followers on his LinkedIn Account. where he shares tips and tricks on Microsoft Excel and other Office Apps.

Michael Olafusi is a 9x Microsoft Most Valuable Professional (MVP) and a business intelligence consultant. He is the lead consultant and founder of MHS Analytics Inc. in Canada and UrBizEdge Limited. He has been consulting for clients across North America, Europe, and Africa on data analysis, business intelligence, and financial modeling for the past 10 years. Outside of his consulting business, he is a member of Rotary and the Southern Cruisers Riding Club (SCRC) Chapter 373. He is a proud member of the Canadian Red Cross friendly calls volunteer team. He is also a faculty member at WorldQuant University, USA.

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