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.
The 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.
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.
(N.B. Please use the Look Inside option to see further chapters)
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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