Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages Paperback – 29 Mar. 2024

The book author has a strong hold over the Powerbi community and even the technology I believe this book is beneficial for people who have had a strong command over the Power BI, R and Python space because of the diversity it brings throughout the chapters, the most important thing is the journey of different libraries and how it has affected the whole space and how the case studies have been shared throughout the book. Congratulations to the authors for binding in a book of such quality!

I have had the opportunity to read "Extending Power BI with Python and R" by Luca Zavarella, and it has quickly become an invaluable resource in my professional library. As someone who works extensively in data analysis and business intelligence, this book provides a comprehensive guide to enhancing Power BI's capabilities using Python and R.Luca Zavarella does an excellent job of explaining complex concepts in a clear and accessible manner. The integration of Python and R into Power BI is covered in depth, with practical examples that are easy to follow. This book is perfect for advanced users looking to take their data visualization and analysis to the next level.The step-by-step tutorials, combined with real-world use cases, make this book not only informative but also highly practical. I highly recommend it to anyone seeking to expand their Power BI skills with advanced analytics and custom visuals.

As a Power Platform consultant I've tended to focus more on automation (Power Apps, Power Automate, etc) over the last few years however I would be nowhere without Power BI. It's role in my journey from a Citizen Dev to a Senior role with a consultancy cannot be underestimated - it gave me life!Circling back round to Power BI and in particular the role of Python and R with I was delighted to be offered the opportunity to read "Extending Power BI with Python and R", 2nd edition.The book provides a comprehensive guide to integrating Python and R with Power BI, offering practical examples (always a great feature of Packt reference materials) that help bring the concepts to life.It covers a wide range of topics, from data ingestion and transformation to advanced analytics and data protection.The book's focus on performance enhancement and large dataset management was particularly interesting. The inclusion of personal data de-identification methods adds an important consideration to the management of data that reflects the growing importance of overall data privacy/sensitivity.Overall, this book is a solid choice for anyone looking to leverage Python and R in Power BI. 😊

I've used Power BI for a number of years and have a basic knowledge of Python but have been keen to start to use 2 tools hand in hand.This is a great book to get started and upskill - I like the GitGub links for test files and it really does well at outlining the use cases for Python in Power BI and stepping through configuring everything and starting to use Python effectively and much clearer than many online guides I've come across.The complexity does increase as you work through the book but is well broken out into discrete chapters.The screenshots are nice and clear with good contrasts on the colours and the language is very clear.At the end of each chapter there's a knowledge check section Q&A which has been helpful in getting up the learning curve.Overall I think this is a great addition to the bookshelf and covers a highly complex area very well.

A great thanks to Vignesh Raju 💯🚀🎯📈 and the Packt team for yet another reading opportunity whilst on my holiday to Thailand, Vietnam, Malaysia and Singapore.Extending Power BI with Pythonand R, Second Edition by Luca ZavarellaPerform advanced analysis using the power of analytical language22 chapters all filled with step by step guidesI have only briefly used R and Python to interact with data and never in the field so it was a nice reflection on something only probably a year ago I tried to learn but never got the chance, this book gave me the inspiration and insight to begin that journey yet again.Highlights for me wereWhere and How to Use R and Python Scripts in Power BIConfiguring R with Power BIAnonymizing and Pseudonymizing Your Data inPower BI where the use of Data masking is shown with great examples also Data perturbation, Tokenization, Hashing, Encryption then a step by step with R and Python really great comparisonsLoading Large Datasets Beyondthe Available RAM in Power BI with a great 30gb example of US flight data provided by Microsoft great use case with Dask and Apache Arrow not something I was aware of before always great to learn about new thingsCalling External APIs to EnrichYour Data calling REST APIsCalculating Columns UsingComplex Algorithms: Distance to calculate Spherical trigonometry very interesting subject reminds me of my days in Access SQL in a mobile phone mapping routine to plot sites within a certain distance.Overall a great book with loads of learning and examples to go at would recommend anyone buying this book.