Book Image

Mastering Microsoft Power BI – Second Edition - Second Edition

By : Gregory Deckler, Brett Powell
4.5 (2)
Book Image

Mastering Microsoft Power BI – Second Edition - Second Edition

4.5 (2)
By: Gregory Deckler, Brett Powell

Overview of this book

Mastering Microsoft Power BI, Second Edition, provides an advanced understanding of Power BI to get the most out of your data and maximize business intelligence. This updated edition walks through each essential phase and component of Power BI, and explores the latest, most impactful Power BI features. Using best practices and working code examples, you will connect to data sources, shape and enhance source data, and develop analytical data models. You will also learn how to apply custom visuals, implement new DAX commands and paginated SSRS-style reports, manage application workspaces and metadata, and understand how content can be staged and securely distributed via Power BI apps. Furthermore, you will explore top report and interactive dashboard design practices using features such as bookmarks and the Power KPI visual, alongside the latest capabilities of Power BI mobile applications and self-service BI techniques. Additionally, important management and administration topics are covered, including application lifecycle management via Power BI pipelines, the on-premises data gateway, and Power BI Premium capacity. By the end of this Power BI book, you will be confident in creating sustainable and impactful charts, tables, reports, and dashboards with any kind of data using Microsoft Power BI.
Table of Contents (18 chapters)
16
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17
Index

Preparing Data Sources

This chapter follows on from the dataset planning process described in Chapter 1, Planning BI Projects, by providing guidance on how to prepare for connecting to and transforming data using Power Query (M) queries. Power Query queries are written in a data transformation language commonly called “M” or can be generated via the Power Query Editor user interface. These queries access data sources and optionally apply data transformation logic to prep the tables for the Power BI data model.

As mentioned in Chapter 1, Planning BI Projects, to the greatest extent possible data transformation processes should be implemented within data sources such as Azure SQL and Azure Synapse SQL rather than via Power BI’s data transformation capabilities. The presence of significant data transformation logic (for example, joins, filters, and new columns) outside of an organization’s primary data warehouse or “source of truth” makes...