Power BI Data Modeling Nisal Mihiranga
- Autor:
- Nisal Mihiranga
- Wydawnictwo:
- BPB Publications
- Ocena:
- Stron:
- 314
- Dostępne formaty:
-
ePubMobi
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Opis
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Power BI Data Modeling
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. Table of Contents
1. Introduction to Microsoft Power BI
2. Microsoft Power BI Eco-system
3. Getting Started with Power BI and Connect with Data
4. My first Power BI Report
5. Intro to BI Building Blocks & Dimensional Mod Concepts
6. Get Data from Relational Databases
7. Cleansing, Blending and Transform Data using Power Query
8. Build Relationships
9. Introduction to DAX and Calculated Columns, Cal Measures & Hierarchies
10. Create Insightful Visuals
11. Row-level Security
12. Calculation Groups in Power BI
13. Self-service AI in Power BI
14. Incremental Refresh for Scalable Models
15. Composite Models & Implement Aggregations to Improve query performance
16. Self-service Data Prep for Any Data
17. Optimize DAX
18. Collaborate Your Power BI Workload
19. Performance Tuning via optimizing Storage and Memory
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. Table of Contents
1. Introduction to Microsoft Power BI
2. Microsoft Power BI Eco-system
3. Getting Started with Power BI and Connect with Data
4. My first Power BI Report
5. Intro to BI Building Blocks & Dimensional Mod Concepts
6. Get Data from Relational Databases
7. Cleansing, Blending and Transform Data using Power Query
8. Build Relationships
9. Introduction to DAX and Calculated Columns, Cal Measures & Hierarchies
10. Create Insightful Visuals
11. Row-level Security
12. Calculation Groups in Power BI
13. Self-service AI in Power BI
14. Incremental Refresh for Scalable Models
15. Composite Models & Implement Aggregations to Improve query performance
16. Self-service Data Prep for Any Data
17. Optimize DAX
18. Collaborate Your Power BI Workload
19. Performance Tuning via optimizing Storage and Memory
Szczegóły książki
- ISBN Ebooka:
- 978-93-893-2883-7, 9789389328837
- Data wydania ebooka :
-
2024-12-18
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- Rozmiar pliku Mobi:
- 11.7MB
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