Data Analysis in Power BI
Apress (Verlag)
978-1-4842-9370-6 (ISBN)
- Noch nicht erschienen - erscheint am 14.06.2026
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You know Power BI’s reputation as a reporting, dashboarding, and data visualization tool but it might not occur to you that it has great value as a tool for data exploration.
Welcome to the first book to explore the powerful tools within Power BI that can enhance and improve your analytical data exploration.
You know Power BI’s reputation as a reporting, dashboarding, and data visualization tool but it might not occur to you that it has great value as a tool for data exploration. This book examines Power BI’s data analysis features and shows you, through real-world examples, how Power BI can be a go-to analysis tool for business users in all domains.
You will discover that Microsoft’s Power BI offers all the number-crunching power of Excel plus versatile and impactful visualization tools that will greatly enhance your discovery process and make it easier to communicate results. You will see that its data analysis expression (DAX) language is far richer and more powerful than Excel’s limited (and outdated) MDX; and its data ingestion utility is vastly superior. You will learn how to unearth unexpected trends and hidden correlations that might be elusive in the numbers but will emerge in high relief using visualization, speeding up analysis and making your data analysis far more complete. You will build analysis pages which, after you have completed a particular analysis, can be preserved along with your datasets for later use, and even passed along to others in an organization as “what-if” tools.
Hands-on exercises are provided that use downloadable data sources and “starter” configurations of Power BI files for building sample analyses. Downloadable Excel samples of those same exercises are provided for easy comparison.
What You Will Learn
Understand the exploratory methodology
Build data sets and take a dive into DAX
Add visualization to your analysis process
Incorporate R and Python
Use Power BI to extend your work
Who ThisBook Is For
Any business user who currently performs exploratory data analysis using tools other than Power BI, users who are not currently doing exploratory analysis but understand their data and how it is used and wish to begin studying it, managers and executives who wish to expand their organization’s use of analytics and encourage new skills in their business workforce. Experience with Microsoft Excel is helpful but not essential.
Scott Robinson is an IT veteran with over 20 years of experience in the data architecture and engineering workspace, in a range of industries from healthcare to insurance to supply chain. He also has been a tech writer for 20 years, writing for a broad range of popular tech websites. In addition to his architecture roles, Scott has been a developer, database designer, database administrator, data scientist, cloud technology consultant, and IT trainer. He decided to write this book while working with a group of business analysts in insurance who were frustrated that they had no real options beyond Excel for doing their exploratory work.
Chapter 1: Data Analysis – A Quick Primer.- Chapter 2: Power BI for Data Analysis.- Chapter 3: Building Datasets.- Chapter 4: A DAX Deep-Dive.- Chapter 5: Exploratory Methodology, Power BI-style.- Chapter 6: Adding Visualization to the Analysis Process.- Chapter 7: Bringing in R and Python.- Chapter 8: Using Power BI to Extend Your Work.
| Erscheint lt. Verlag | 14.6.2026 |
|---|---|
| Zusatzinfo | 40 Illustrations, black and white; X, 315 p. 40 illus. |
| Verlagsort | Berkley |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Mathematik / Informatik ► Informatik ► Software Entwicklung | |
| Mathematik / Informatik ► Informatik ► Theorie / Studium | |
| Mathematik / Informatik ► Mathematik ► Finanz- / Wirtschaftsmathematik | |
| ISBN-10 | 1-4842-9370-3 / 1484293703 |
| ISBN-13 | 978-1-4842-9370-6 / 9781484293706 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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