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Extending Power BI with Python and R

You're reading from   Extending Power BI with Python and R Perform advanced analysis using the power of analytical languages

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781837639533
Length 814 pages
Edition 2nd Edition
Languages
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Author (1):
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Luca Zavarella Luca Zavarella
Author Profile Icon Luca Zavarella
Luca Zavarella
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Table of Contents (27) Chapters Close

Preface 1. Where and How to Use R and Python Scripts in Power BI FREE CHAPTER 2. Configuring R with Power BI 3. Configuring Python with Power BI 4. Solving Common Issues When Using Python and R in Power BI 5. Importing Unhandled Data Objects 6. Using Regular Expressions in Power BI 7. Anonymizing and Pseudonymizing Your Data in Power BI 8. Logging Data from Power BI to External Sources 9. Loading Large Datasets Beyond the Available RAM in Power BI 10. Boosting Data Loading Speed in Power BI with Parquet Format 11. Calling External APIs to Enrich Your Data 12. Calculating Columns Using Complex Algorithms: Distances 13. Calculating Columns Using Complex Algorithms: Fuzzy Matching 14. Calculating Columns Using Complex Algorithms: Optimization Problems 15. Adding Statistical Insights: Associations 16. Adding Statistical Insights: Outliers and Missing Values 17. Using Machine Learning without Premium or Embedded Capacity 18. Using SQL Server External Languages for Advanced Analytics and ML Integration in Power BI 19. Exploratory Data Analysis 20. Using the Grammar of Graphics in Python with plotnine 21. Advanced Visualizations 22. Interactive R Custom Visuals 23. Other Books You May Enjoy
24. Index
Appendix 1: Answers
1. Appendix 2: Glossary

Preface

Welcome to the second edition of our book, where the journey into advanced analytics for Power BI deepens and expands your expertise in Python and R. This edition isn’t just an update; it’s an expansion into new territory, meticulously crafted to enhance your analytical prowess, whether you’re using Power BI or diving directly into Python and R.

We’ve introduced new chapters that pave the way for optimizing your environment, harnessing the power of Intel’s Math Kernel Library for speed, and tackling integration challenges with finesse. Imagine managing massive data sets effortlessly, using advanced techniques and the Swift parquet format for fast data processing. Imagine mastering the art of probabilistic fuzzy matching and navigating the potential of SQL Server External Languages to overcome traditional limitations in Power BI. You’ll also be guided in creating stunning visualizations using not only R, but also Python, applying the Grammar of Graphics through a specialized package.

The remaining chapters have been carefully updated, expanded, and technically refined. They give you the skills to excel at validating data using regular expressions, leveraging data from a variety of uncommon external sources, and applying sophisticated data transformation algorithms. You’ll explore advanced methods for protecting personal data in Power BI, including strategies for pseudonymization, anonymization, and data masking. This book also covers integrating external APIs to enrich your datasets, improve I/O efficiency, and leverage the powerful analytical capabilities of Python and R. Perform comprehensive analysis and uncover deep insights with statistical and machine learning methods, all without requiring the premium capacity. The text encourages you to visualize key statistical features of your data through a variety of graphical outputs as you develop machine learning models. In addition, each chapter has challenging questions and answers that reinforce your understanding and test your skills.

Join us on this challenging adventure where your analytical skills will soar to new heights.

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