1 option
Analytics engineering with Microsoft Fabric and Power BI : the definitive guide for building enterprise-grade analytics solutions / by Shabnam Watson and Nikola Ilic.
- Format:
- Book
- Author/Creator:
- Watson, Shabnam, author.
- Ilic, Nikola, author.
- Language:
- English
- Subjects (All):
- Business intelligence--Data processing.
- Business intelligence.
- Business intelligence--Computer programs.
- Information visualization--Computer programs.
- Information visualization.
- Visual analytics.
- Physical Description:
- 1 online resource (450 pages)
- Edition:
- [First edition].
- Place of Publication:
- Santa Rosa, CA : O'Reilly Media, Inc., [2026]
- Summary:
- While Microsoft Power BI has dominated the business intelligence market for years and is a go-to tool for creating visually appealing, interactive reports and dashboards, it's now an integral part of Microsoft Fabric, the end-to-end analytics platform that offers unprecedented flexibility and scalability for building enterprise-grade data analytics solutions. This book covers everything analytics engineers need to know to design and implement robust and efficient analytics solutions using Microsoft Fabric and Power BI. You'll learn the core components of Fabric, such as lakehouses, warehouses, and eventhouses, and how to work with semantic models, ensuring that data is structured and ready for analysis. You'll also discover essential techniques in both Microsoft Fabric and Power BI that you can apply in your day-to-day work. Explore the core components of Microsoft Fabric Implement, manage, and optimize Power BI semantic models Discover numerous architectural solutions with Microsoft Fabric and Power BI Build Fabric items such as lakehouses, warehouses, semantic models, and more, and share them within your organization Identify when to use a particular Fabric item or implement a particular design pattern Implement the analytics development lifecycle Optimize and fine-tune existing analytics solutions.
- Notes:
- OCLC-licensed vendor bibliographic record.
- OCLC:
- 1573519114
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.