Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages...

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Luca Zavarella Rajat Talwar

Extending Power BI with Python and R

Perform advanced analysis using the power of analytical languages

Luca Zavarella, Rajat Talwar

$124.95 $99.70

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English

Packt Publishing Limited
29 March 2024

Operational research; Presentation graphics software; Enterprise software; Computer science

Ingest, transform, manipulate, and visualize your data beyond Power BI's capabilities. Purchase of the print or Kindle book includes a free eBook in PDF format.

Key Features

Discover best practices for using Python and R in Power BI by implementing non-trivial code Enrich your Power BI dashboards using external APIs and machine learning models Create any visualization, as complex as you want, using Python and R scripts

Book DescriptionThe latest edition of this book delves deep into advanced analytics, focusing on enhancing Python and R proficiency within Power BI. New chapters cover optimizing Python and R settings, utilizing Intel's Math Kernel Library (MKL) for performance boosts, and addressing integration challenges. Techniques for managing large datasets beyond available RAM, employing the Parquet data format, and advanced fuzzy matching algorithms are explored. Additionally, it discusses leveraging SQL Server Language Extensions to overcome traditional Python and R limitations in Power BI. It also helps in crafting sophisticated visualizations using the Grammar of Graphics in both R and Python.

This Power BI book will help you master data validation with regular expressions, import data from diverse sources, and apply advanced algorithms for transformation. You'll learn how to safeguard personal data in Power BI with techniques like pseudonymization, anonymization, and data masking. You'll also get to grips with the key statistical features of datasets by plotting multiple visual graphs in the process of building a machine learning model. The book will guide you on utilizing external APIs for enrichment, enhancing I/O performance, and leveraging Python and R for analysis.

You'll reinforce your learning with questions at the end of each chapter.

What you will learn

Configure optimal integration of Python and R with Power BI Perform complex data manipulations not possible by default in Power BI Boost Power BI logging and loading large datasets Extract insights from your data using algorithms like linear optimization Calculate string distances and learn how to use them for probabilistic fuzzy matching Handle outliers and missing values for multivariate and time-series data Apply Exploratory Data Analysis in Power BI with R Learn to use Grammar of Graphics in Python

Who this book is forThis book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.

By: Luca Zavarella
Foreword by: Rajat Talwar
Imprint: Packt Publishing Limited
Country of Publication: United Kingdom
Edition: 2nd Revised edition
Dimensions: Height: 235mm, Width: 191mm,
ISBN: 9781837639533
ISBN 10: 1837639531
Pages: 814
Publication Date: 29 March 2024
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active

Table of Contents Where and How to Use R and Python Scripts in Power BI Configuring R with Power BI Configuring Python with Power BI Solving Common Issues When Using Python and R in Power BI Importing Unhandled Data Objects Using Regular Expressions in Power BI Anonymizing and Pseudonymizing your Data in Power BI Logging Data from Power BI to External Sources Loading Large Datasets Also Beyond the Available RAM in Power BI Boosting Data Loading Speed in Power BI with Parquet Format Calling External APIs To Enrich Your Data Calculating Columns Using Complex Algorithms: Distances Calculating Columns Using Complex Algorithms: Fuzzy Matching Calculating Columns Using Complex Algorithms: Optimization Problems Adding Statistics Insights: Associations Adding Statistics Insights: Outliers and Missing Values Using Machine Learning Without Premium or Embedded Capacity Using SQL Server External Languages for Advanced Analytics and ML Integration in Power BI Exploratory Data Analysis Using the Grammar of Graphics in Python with plotnine Advanced Visualizations Interactive R Custom Visuals

Luca Zavarella has a rich background as an Azure Data Scientist Associate and Microsoft MVP, with a Computer Engineering degree from the University of L'Aquila. His decade-plus experience spans the Microsoft Data Platform, starting as a T-SQL developer on SQL Server 2000 and 2005, then mastering the full suite of Microsoft Business Intelligence tools (SSIS, SSAS, SSRS), and advancing into data warehousing. Recently, his focus has shifted to advanced analytics, data science, and AI, contributing to the community as a speaker and blogger, especially on Medium. Currently, he leads the Data & AI division at iCubed, and he also holds an honors degree in classical piano from the ""Alfredo Casella"" Conservatory in L'Aquila.