Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Architecting Power BI Solutions in Microsoft Fabric
  • Table Of Contents Toc
Architecting Power BI Solutions in Microsoft Fabric

Architecting Power BI Solutions in Microsoft Fabric

By : Nagaraj Venkatesan
5 (1)
close
close
Architecting Power BI Solutions in Microsoft Fabric

Architecting Power BI Solutions in Microsoft Fabric

5 (1)
By: Nagaraj Venkatesan

Overview of this book

Business Intelligence (BI) tools like Power BI are used by a wide range of professionals, creating diverse and complex scenarios, and finding the right solution can be daunting, especially when multiple approaches exist for a single use case. The author distills his 17 years of experience on various data platform technologies in this book to walk you through various Power BI usage scenarios. The book is structured around Power BI usage scenarios, such as developing solutions for corporate BI reporting, self-service BI reporting, and Power BI for data scientists and independent software vendors (ISVs). Each part highlights common data issues encountered in the usage scenario, the correct approach to solve the problems, and supporting technical guidance. The chapters also introduce you to some of the latest enhancements in Power BI, such as Microsoft Fabric integration with Power BI, AI features like Copilot, Power BI Git integration, and Power BI Governance features. By the end of this book, you’ll have learned how to design optimal solutions using Power BI components and pick the right tool for the job, while adhering to security and performance best practices. *Email sign-up and proof of purchase required
Table of Contents (26 chapters)
close
close
Lock Free Chapter
1
Part 1: Power BI Fundamentals
6
Part 2: Designing Enterprise BI Solutions
14
Part 3: Power BI for Business Users
17
Part 4: Power BI for Data Scientists
19
Part 5: Power BI for Administrators

Decoding the data science process

Data science is the systematic process of getting valuable insights out of data. However, you may ask, isn’t it the same thing we do in Power BI or any other data engineering process? The key difference is that data science involves advanced techniques such as machine learning and deep learning, which are powered by complex statistical formulas to predict/forecast valuable insights out of data, while in data engineering the focus is to ingest, process, and model the data in a presentable way (for example, as facts and dimensions) for business intelligence applications. In data science, we are expected to predict outcomes/values or results (things such as the price of the stock in 6 months, which team is likely to win the match, and so on) based on the data available, while data engineering presents existing data in a way that makes it easier to gain insights. Hence, the process involved and tools used in a data science project are different...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Architecting Power BI Solutions in Microsoft Fabric
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon