Book Image

Mastering Microsoft Power BI

By : Brett Powell
5 (1)
Book Image

Mastering Microsoft Power BI

5 (1)
By: Brett Powell

Overview of this book

This book is intended for business intelligence professionals responsible for the design and development of Power BI content as well as managers, architects and administrators who oversee Power BI projects and deployments. The chapters flow from the planning of a Power BI project through the development and distribution of content to the administration of Power BI for an organization. BI developers will learn how to create sustainable and impactful Power BI datasets, reports, and dashboards. This includes connecting to data sources, shaping and enhancing source data, and developing an analytical data model. Additionally, top report and dashboard design practices are described using features such as Bookmarks and the Power KPI visual. BI managers will learn how Power BI’s tools work together such as with the On-premises data gateway and how content can be staged and securely distributed via Apps. Additionally, both the Power BI Report Server and Power BI Premium are reviewed. By the end of this book, you will be confident in creating effective charts, tables, reports or dashboards for any kind of data using the tools and techniques in Microsoft Power BI.
Table of Contents (15 chapters)

Query folding

Query folding is one of the most powerful and important capabilities of the M language as it translates M expressions into SQL statements that can be executed by the source system. With query folding, M serves as an abstraction layer to implement both common and complex data cleansing and transformation operations while still leveraging source system resources. When implementing any remaining logic or data transformations via M functions, a top priority of the dataset designer is to ensure that these operations are folded to the data source.

In the following M query, a Table.RemoveColumns() M function is applied against the SQL view for the Internet Sales fact table to exclude three columns that are not needed for the dataset:

Power Query Editor: View Native Query

The additional step is translated to a SQL query that simply doesn't select the three columns...