Book Image

Expert Data Modeling with Power BI

By : Soheil Bakhshi
Book Image

Expert Data Modeling with Power BI

By: Soheil Bakhshi

Overview of this book

This book is a comprehensive guide to understanding the ins and outs of data modeling and how to create data models using Power BI confidently. You'll learn how to connect data from multiple sources, understand data, define and manage relationships between data, and shape data models to gain deep and detailed insights about your organization. In this book, you'll explore how to use data modeling and navigation techniques to define relationships and create a data model before defining new metrics and performing custom calculations using modeling features. As you advance through the chapters, the book will demonstrate how to create full-fledged data models, enabling you to create efficient data models and simpler DAX code with new data modeling features. With the help of examples, you'll discover how you can solve business challenges by building optimal data models and changing your existing data models to meet evolving business requirements. Finally, you'll learn how to use some new and advanced modeling features to enhance your data models to carry out a wide variety of complex tasks. By the end of this Power BI book, you'll have gained the skills you need to structure data coming from multiple sources in different ways to create optimized data models that support reporting and data analytics.
Table of Contents (18 chapters)
Section 1: Data Modeling in Power BI
Section 2: Data Preparation in Query Editor
Section 3: Data Modeling
Section 4: Advanced Data Modeling

Naming conventions

It is essential to have naming conventions for Power BI developers and data modelers. It helps with solutions' consistency and makes the code more readable and more understandable for the support specialists. It also sets common ground that everyone across the organization interacting with our Power BI solutions can benefit from.

Data sources do not necessarily have the most user-friendly names. So, it is essential to follow a predefined naming convention during development, which will help the support specialists and contributors create new reports on top of an existing dataset. The following naming convention is suggested:

  • Use camel case for object names including table names, column names, and parameter names.
  • Replace underscores, dashes, hyphens, or dots between the words with space.
  • Remove prefixes and suffixes from table names (such as DimDate becoming Date or FactSales becoming Sales).
  • Use the shortest and most self-explanatory...