Advanced Analytics with Power BI and Excel: Learn powerful visualization and data analysis techniques using Microsoft BI tools along with Python and R - Paperback

by Dejan Sarka (Author), Jernej Rihar (Author), Klemen Vončina (Author)

Empowering You to Master Business Intelligence and Solve Real-world Analytical Problems.

DESCRIPTION

In today's analytics landscape, proficiency in Excel and Power BI is practically a prerequisite for a successful career. This book provides a concise yet comprehensive exploration of these foundational elements of modern Business Intelligence (BI).

Comprising ten chapters, this book covers the entire development journey of a Power BI analytical solution, spanning from data modeling and preparation to report creation, publication, and dashboard and app deployment. It offers insights into security measures and performance optimization, ensuring a well-rounded understanding of the BI ecosystem. Furthermore, it delves into advanced topics, such as leveraging data science algorithms within reports, offering readers an extensive learning experience.

The book takes a holistic approach to these technologies, offering a contrast to the narrow perspectives often adopted by contemporary BI professionals who rely solely on a single tool or language. The book allows data enrichment through calculations that can be achieved using various languages, including SQL queries at the source, Power Query Formula Language, M, Python, R, and DAX. By the end of this book you will master these options but be able to also weigh their pros and cons to make informed decisions.

TABLE OF CONTENTS

1. Introducing the Theoretical Background for Democratizing Analytics

2. Acquiring and transforming data from multiple sources

3. Power Query Transformations and Formula Language (M) Overview

4. Building a simple analytical solution with Power Pivot in Excel

5. Enhancing the model and business analysis with DAX

6. Creating reports in Power BI Desktop

7. Using the Power BI Service

8. Data Science in Power BI

9. Optimizing Power BI models and reports

10. Deploying, Maintaining and Securing Power BI Assets

Index