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Key benefits

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

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.

Who is this book for?

If 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.

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

What do you get with Print?

Instant access to your digital eBook copy whilst your Print order is Shipped

Colour book shipped to your preferred address

Download this book in EPUB and PDF formats

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AI Assistant (beta) to help accelerate your learning

Frequently bought together

€41.99

€27.99

Mastering Microsoft Power BI – Second Edition

€37.99

Total € 107.97

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Amazon verified reviews

YAS May 07, 2024

I have been in analytics for well over two decades and this book is a must have for anyone in data analysis career stack. While this book focuses on the Power Bi stack, the techniques can be applied to others. This is what makes the book invaluable. Two major pitfalls one have to avoid, if possible, when writing, any data analysis book deals with being technically dense and long chapters. This work by Guz avoided these pitfalls.I really enjoyed the portion on how to use other Microsoft tools such as Power Automate to clean data. This is a hidden gem that I haven't fully utilized but will do in the near future. I also like the chapter on how to use AI to help in data cleansing. I believe this is invaluable in understanding how your data is structured and how AI can help you identify many anomalies.In conclusion, whether you are a novice starting on your data analysis journey or have been doing thi a long as I have, Guz has done a wonderful job on balancing both audiences. I wholeheartedly recommend this book be part of your reference library.--Yuhanna Sherriff

Amazon Verified review

ebun Apr 17, 2024

The book stands out as a data cleaning guide for your data cleaning task using Power BI. It starts from the very start of data issues, which involve data quality checks, to more advanced approaches like automating data cleaning tasks with Power Automate.One great thing about the book is its focus on data cleaning tasks, which makes it interesting to read about one of the most laborious tasks in the data field in a one-stop book.One aspect that I enjoyed most was the use of Table.Split functions, which were emphasized in the book to reduce query execution times by dividing large table into smaller partitions and enable parallel processing, are used to handle complex transformations.If you are passionate about M query optimization, there are goodies for you in this book.If you deal with data regularly, I can bet this is one of the books to have either to learn more or refresh your skills.

Amazon Customer Jul 28, 2024

Data Cleaning with Power BI is a comprehensive guide that brilliantly covers all facets of data preparation and management within Power BI. Starting with the fundamentals of Power Query and DAX, the book delves into the critical aspects of data quality, providing practical steps for detecting issues early and maintaining data integrity. The sections on advanced techniques, including the use of R, Python, and AI, are particularly enlightening. Whether you're new to data cleaning or looking to refine your skills, this book is an invaluable resource for ensuring your data is accurate, reliable, and actionable.

TickboxPhil Apr 28, 2024

This book manages to widen the focus from straight Power Query methods through data quality and modelling, so more than just the M language. But as M / Power Query is now included in Azure Data Factory as a full ETL solution, that's what makes it interesting to me again (together with alternatives like dbt and core Python code). Also included here is the newer Exploratory Data Analysis functionality and extras like fuzzy matching and fill down, integration of Python/R scripts etc (although watch out for Microsoft’s changing platform provision due to Fabric). Advanced methods like custom queries (including some web scraping), optimisation and data modelling are handled very practically. Paginated Reports is something invariably left out of Power BI but useful for real business, and Power Automate (eg. triggered on new data, and an interesting take on snapshotting) is also fully demonstrated. OpenAI’s ChatGPT and CoPilot are then brought in through Azure to contribute a further useful role.I did have to prod the author to get his GitHub repo cleaned up for data linking, but this book only recently published and he was very responsive and did the job – another bonus resource. Also, a fair amount of overview on data quality and ethics may get in the way of experienced data pro's but it's a good place to include it. The main text itself though operates at a detail level full of tips, and works nicely. I expected just a Power Query crash course, but was pleasantly surprised to find this wider angle, so well worth working through this useful guide.

Sivanagaraju Gadiparthi Jul 13, 2024

"Data Cleaning with Power BI" by Gus Frazer is an indispensable guide for anyone looking to transform messy data into valuable insights. Published by Packt Publishing in February 2024, this book meticulously covers the essential aspects of data cleaning using Power BI, making it a must-read for data analysts, business intelligence professionals, and data scientists.Gus Frazer, an experienced analytics consultant, leverages his extensive background to provide a comprehensive manual that demystifies the complexities of data cleaning. The book is structured to take readers from the fundamentals to advanced techniques, ensuring a robust understanding of data quality issues and the importance of data cleaning.The initial chapters focus on the basics, such as understanding data quality and the principles of data cleaning. Frazer emphasizes the significance of clean data in decision-making and business outcomes, setting a strong foundation for the more technical content that follows. He provides practical insights into common data quality issues and effective strategies for addressing them.As the book progresses, Frazer delves into the technical aspects of Power BI, covering essential tools like Power Query and DAX. The chapters on data transformations and the M language are particularly valuable, offering detailed explanations and hands-on examples that help readers apply these techniques in real-world scenarios.The later chapters introduce more advanced topics, including the use of R and Python scripts for data cleaning and the integration of machine learning techniques. Frazer's step-by-step approach and clear explanations make these complex subjects accessible to readers with varying levels of expertise."Data Cleaning with Power BI" stands out for its practical approach, real-world examples, and the author's ability to convey complex information clearly and effectively. It's not just a technical manual but a roadmap for anyone looking to enhance their data cleaning skills using Power BI.

Data Cleaning with Power BI: The definitive guide to transforming dirty data into actionable insights

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