Название: Advanced Analytics with Power BI and Excel: Learn Powerful Visualization and Data Analysis Techniques Using Microsoft BI Tools along with Python and RАвтор: Dejan Sarka, Jernej Rihar, Klemen Voncina
Издательство: Orange Education Pvt Ltd
Год: 2023
Страниц: 295
Язык: английский
Формат: pdf, epub
Размер: 17.0 MB
Empowering You to Master Business Intelligence and Solve Real-world Analytical problems.
Book 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.
Besides report elements like tables, matrices and graphs, you can use Power BI as an advanced data science tool. This chapter introduces advanced analytics capabilities in the core Power BI and shows what you can do with the help of external languages, namely R and Python, or external services that include Azure Artificial Intelligence. The real data science power comes to Power BI with the support for R and Python languages. Both languages are very popular and both have really strong support for data science. Of course, you can use both languages without Power BI. However, besides Power BI, you can also run R and Python code inside SQL Server, by using SQL Server Machine Learning Services. In order to follow the examples in this chapter, you should have SQL Server Machine Learning Services, R and Python installed. To install all of these, please follow the Install SQL Server 2022 Machine Learning Services (Python and R) on Windows article on MS Learn.
or the demos in this chapter, you should also install the following packages (or libraries) in the same way as it is described in the MS Learn article for the RevoScaleR and revoscalepy packages (please note that both languages are case sensitive, so you have to type the package names exactly as they are written here):
• For R, we are going to use the RODBC, reshape2, dplyr and rpart.plot libraries.
• For Python, you need the NumPy, Pandas, Matplotlib, Seaborn and Sklearn libraries.
Finally, for code development in R, we used RStudio Desktop free version by Posit, and for Python development, we used Visual Studio Code.
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
Скачать Advanced Analytics with Power BI and Excel: Learn Powerful Visualization and Data Analysis Techniques Using Microsoft BI Tools