Power BI Data Modeling:: Build Interactive Visualizations, Learn DAX, Power Query, and Develop BI Models
- Length: 314 pages
- Edition: 1
- Language: English
- Publisher: BPB Publications
- Publication Date: 2022-03-21
- ISBN-10: 9389328837
- ISBN-13: 9789389328837
- Sales Rank: #2358766 (See Top 100 Books)
Build Power BI Models Efficiently and Effectively
Key Features
- Extensive examples illustrating Power BI and data modeling concepts.
- Includes graphical images and explanations of using Power BI.
- Numerous hands-on practical examples are teaching best practices in predictive modeling.
Description
Creating data models has never been straightforward. This book demonstrates how to formulate a complete business analytics model that combines several data sources, executes numerous computations, and scales across hundreds of BI users.
To begin, you’ll learn about the Microsoft Power BI ecosystem by downloading the Power BI desktop and exploring all of its features and capabilities. Through examples, you’ll learn how to connect to databases of Excel; and SQL Server, shaping the data with Power Query, and then transforming the data into actionable information. You will gain knowledge of the DAX language by exploring it, writing DAX functions, and creating hierarchies. You will be trained to develop effective business intelligence models by studying numerous data modeling topics.
You get to put professionals’ best practices to the test when handling large data scenarios and executing analytics on top of them. Additionally, the book discusses how to scale Power BI while considering its storage, memory, and security requirements. You’ll see that several new topics have been included, including performance tuning, DAX Studio, sharing Power BI reports, and publishing reports to Sharepoint online.
What you will learn
- Conduct profiling, cleansing, and transformation of data.
- Build data models, aggregate data, and create hierarchies.
- Practice DAX language, write calculations, and execute them.
- Utilize advanced features including AI visualizations and performance analyzer.
- Examine various connection types and connect data from different sources.
- Enhance performance by boosting storage and memory.
Who this book is for
This book is intended for data analysts, business analysts, and any other business user who are interested in learning how to develop data models using Power BI from beginning to end. To follow this book and master Power BI, a basic understanding of data visualization would be sufficient.
Cover Page Title Page Copyright Page Dedication Page About the Author About the Reviewer Acknowledgement Preface Errata Table of Contents 1. Introducing Microsoft Power BI Structure Objective Business intelligence History of Business Intelligence Business Intelligence process Self-service BI Introducing Power BI Components in Power BI Why does Power BI stand out from other BI tools in the market? Conclusion Questions Answers 2. Power BI Ecosystem Structure Objectives Power BI ecosystem Power BI desktop Power BI service Power BI mobile Conclusion Questions Answers 3. Getting Started with Power BI and Connect with Data Structure Objective Get data Power BI connectors Connection types Conclusion Questions Answers 4. My First Power BI Report Structure Objective Download the demo materials Load data into Power BI Data cleansing and blending Create product hierarchy Create calculations Data visualizing Add a map visual Add a clustered column chart Add a matrix visual Cross filtering Drill-down Add a slicer Conclusion Questions Answers 5. Introducing BI Building Blocks: Dimensional Modeling Concepts Structure Objective What is data modeling, and why? Classic BI approach Modern self-service BI approach End-to-end BI with Microsoft Power BI Data warehouse Bus matrix architecture Fact tables Dimension tables Granularities Star schema Snowflake schema Conclusion Questions Answers 6. Get Data from Relational Databases Structure Objective Relational database connectors Getting data with SQL Server database Conclusion Questions 7. Cleansing, Blending, and Transforming Data Using Power Query Structure Objective Introducing Power Query Business scenario Connect to the database and extract tables Data cleansing Work with budget data Conclusion Questions Answer 8. Build Relationships Structure Objective Relationships in Power BI Methods of creating relationships Demystify relationships in Power BI Select cardinality of a relationship Select cross filter direction Active and inactive relationships Conclusion Questions 9. Introducing DAX, Calculated Columns, Calculated Measures, and Hierarchies Structure Objective Calculations in Power BI Calculated columns Calculated measures Calculated tables Hierarchies Conclusion Questions 10. Creating Insightful Reports Using Visualization Techniques Structure Objective Data visualization practices Designing the report Filtrations Use slicers in the report Cross-filtering Drill-down visuals Drill-through visuals Theming Mobile layout Conclusion Questions 11. Row-Level Security in Power BI Structure Objective Security overview Static row-level security—role-based Creating roles How to test raw-level security? Dynamic row-level security Conclusion Questions 12. Calculation Groups in Power BI Structure Objective Calculation groups requirement Calculation groups and how it works? Creating calculation groups in Power BI Sorting the calculated items Limitations in calculation groups Conclusion Questions 13. Self-service AI Capabilities in Power BI Structure Objectives Introducing AI capabilities in Power BI Quick insights Q&A visual in Power BI Q&A visual in the Power BI desktop Decomposition tree visual Key influencer Smart narrative Perform text analytics, vision, and Azure Machine Learning R and Python integration Conclusion Questions 14. Incremental Refresh for Data Models Structure Objective Data refresh requirement Incremental data refresh requirement Configuring incremental refresh Defining the filter parameters Applying filter using parameters Defining incremental refresh policy Conclusion Questions 15. Composite Models and Perform Aggregations to Improve Query Performance Structure Objective Prerequisites Connection types—recap Import DirectQuery Demo database Let us consume the demo database using Power BI Let us build aggregations Add newly created aggregated table into model How to determine whether the aggregation table is used by the Power BI engine or not? Power BI performance analyzer How to configure aggregations? Let us try some advanced aggregations Composite models Composite models explained Configure storage mode Force engine to select right aggregation table Composite models allow to achieve balanced architecture Conclusion Questions 16. Self-service Data Preparation for Any Data Structure Objective Introducing citizen ETLing Why self-service data preparation? Creating dataflows in Power BI ETL for large data sets Conclusion Questions 17. Optimize DAX Structure Objective Basic optimization and techniques Clear cache Measure the performance Optimize DAX syntax DAX functions optimization Conclusion Questions 18. Collaborating Your Power BI Workload Structure Objective Power BI Workspace 101 Creating a workspace Data gateway configurations Sharing Power BI content Share with a website or portal Share dashboards Power BI app Conclusion Questions 19. Performance Tuning via Optimizing Storage and Memory Structure Objective Introducing VertiPaq engine Single table versus star schema model Filter only required data for analysis Applying correct data types Creating custom columns in Power Query Using subset of data Disabling the Power Query load Limiting distinct columns as much as possible Conclusion Question Index
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