Publisher's Synopsis
Ingest, transform, manipulate, and visualize your data beyond Power BI's capabilities
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 Description
With this updated second edition, you'll not only learn how to configure the Power BI environment to run Python and R scripts at peak performance-you'll also become familiar with the appropriate solutions to the most common problems you may encounter. Extending Power BI with Python and R explores data ingestion and data transformation extensions before moving on to focus on data enrichment and data visualization. You'll learn how to ingest data larger than available memory, import data from external sources, and transform data using complex algorithms, as well as implementing personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll find out how to call external APIs to enrich your data much faster, and address I/O performance issues using Python and R. Next, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also get to grips with the key statistical features of data sets by plotting multiple visual graphs in the process of building a machine learning model. Your knowledge will be tested through questions and answers at the end of each chapter. By the end of this book, you'll be able to enrich your Power BI data models and unlock valuable insights using Python and R.What you will learn
- Perform complex data manipulations not possible by default in Power BI
- Apply data anonymization and data pseudonymization in Power BI
- Log data and load large datasets in Power BI using Python and R
- Extract insights from your data using linear optimization and other algorithms
- Calculate string distances and learn how to use them for fuzzy matching and fuzzy clustering
- Handle outliers and missing values for multivariate and time-series data
- Apply Exploratory Data Analysis in Power BI with R
Who this book is for
This 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.
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