Data Cleaning with Power BI
Packt Publishing Limited (Verlag)
978-1-80512-640-9 (ISBN)
Key Features
Implement best practices for connecting, preparing, cleaning, and analyzing multiple sources of data using Power BI
Conduct exploratory data analysis (EDA) using DAX, PowerQuery, and the M language
Apply your newfound knowledge to tackle common data challenges for visualizations in Power BI
Purchase of the print or Kindle book includes a free PDF eBook
Book DescriptionMicrosoft 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.What you will learn
Connect to data sources using both import and DirectQuery options
Use the Query Editor to apply data transformations
Transform your data using the M query language
Design clean and optimized data models by creating relationships and DAX calculations
Perform exploratory data analysis using Power BI
Address the most common data challenges with best practices
Explore the benefits of using OpenAI, ChatGPT, and Microsoft Copilot for simplifying data cleaning
Who this book is forIf you’re a data analyst, business intelligence professional, business analyst, data scientist, or anyone who works with data on a regular basis, this book is for you. It’s a useful resource for anyone who wants to gain a deeper understanding of data quality issues and best practices for data cleaning in Power BI. If you have a basic knowledge of BI tools and concepts, this book will help you advance your skills in Power BI.
Gus Frazer is a seasoned analytics consultant who focuses on business intelligence solutions. With over eight years of experience working for the two market-leading platforms, Power BI (Microsoft) and Tableau, he has amassed a wealth of knowledge and expertise. He also has experience in helping hundreds of customers to drive their digital and data transformations, scope data requirements, drive actionable insights, and most important of all, clean data ready for analysis.
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
| Erscheinungsdatum | 06.01.2024 |
|---|---|
| Verlagsort | Birmingham |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Informatik ► Software Entwicklung ► User Interfaces (HCI) | |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| ISBN-10 | 1-80512-640-7 / 1805126407 |
| ISBN-13 | 978-1-80512-640-9 / 9781805126409 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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