Data cleaning with Power BI : the definitive guide to transforming dirty data into actionable insights
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Format
Edition
First edition.
Language
English
ISBN
9781805126058, 1805126059
Notes
Bibliography
Includes bibliographical references and index.
Description
Microsoft Power BI offers a range of powerful data cleaning and preparation options through tools such as DAX, Power Query, and the M language. However, despite its user-friendly interface, mastering it can be challenging. Whether you're a seasoned analyst or a novice exploring the potential of Power BI, this comprehensive guide equips you with techniques to transform raw data into a reliable foundation for insightful analysis and visualization. This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You'll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you'll explore Power BI's data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you'll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier. By the end of the book, you will have a comprehensive understanding of data cleaning concepts, techniques, and how to use Power BI and its tools for effective data preparation.
Local note
O'Reilly,O'Reilly Online Learning: Academic/Public Library Edition
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Citations
APA Citation, 7th Edition (style guide)
Frazer, G. (2024). Data cleaning with Power BI: the definitive guide to transforming dirty data into actionable insights (First edition.). Packt Publishing Ltd..
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Frazer, Gus. 2024. Data Cleaning With Power BI: The Definitive Guide to Transforming Dirty Data Into Actionable Insights. Birmingham, UK: Packt Publishing Ltd.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Frazer, Gus. Data Cleaning With Power BI: The Definitive Guide to Transforming Dirty Data Into Actionable Insights Birmingham, UK: Packt Publishing Ltd, 2024.
Harvard Citation (style guide)Frazer, G. (2024). Data cleaning with power BI: the definitive guide to transforming dirty data into actionable insights. First edn. Birmingham, UK: Packt Publishing Ltd.
MLA Citation, 9th Edition (style guide)Frazer, Gus. Data Cleaning With Power BI: The Definitive Guide to Transforming Dirty Data Into Actionable Insights First edition., Packt Publishing Ltd., 2024.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
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Grouped Work ID
f058389d-ec58-01d7-898b-a5d0ecfaee43-eng
Grouping Information
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|---|---|
| Full title | data cleaning with power bi the definitive guide to transforming dirty data into actionable insights |
| Author | frazer gus |
| Grouping Category | book |
| Last Update | 2024-12-17 08:40:50AM |
| Last Indexed | 2024-12-17 08:46:30AM |
Book Cover Information
| Image Source | google_isbn |
|---|---|
| First Loaded | Dec 17, 2024 |
| Last Used | Dec 23, 2024 |
Marc Record
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| 250 | |a First edition. | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Table of Contents Introduction to Power BI Data Cleaning Understanding Data Quality and Why Data Cleaning is Important Data Cleaning Fundamentals and Principles The Most Common Data Cleaning Operations Importing Data into Power BI Cleaning Data with Query Editor Transforming Data with the M Language Using Data Profiling for Exploratory Data Analysis (EDA) Advanced Data Cleaning Techniques Creating Custom Functions in Power Query M Query Optimization Data Modeling and Managing Relationships Preparing Data for Paginated Reporting Automating Data Cleaning Tasks with Power Automate Making Life Easier with OpenAI. | |
| 520 | |a Microsoft Power BI offers a range of powerful data cleaning and preparation options through tools such as DAX, Power Query, and the M language. However, despite its user-friendly interface, mastering it can be challenging. Whether you're a seasoned analyst or a novice exploring the potential of Power BI, this comprehensive guide equips you with techniques to transform raw data into a reliable foundation for insightful analysis and visualization. This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You'll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you'll explore Power BI's data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you'll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier. By the end of the book, you will have a comprehensive understanding of data cleaning concepts, techniques, and how to use Power BI and its tools for effective data preparation. | ||
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