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Mastering Microsoft Power BI

Mastering Microsoft Power BI - Second Edition

By : Greg Deckler, Brett Powell
4.6 (56)
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Mastering Microsoft Power BI

Mastering Microsoft Power BI

4.6 (56)
By: Greg 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)
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Index

Optimizing data model performance

One of the main reasons for creating a dataset, particularly an import mode dataset, is to provide a performant data source for reports and dashboards. Although Power BI supports traditional reporting workloads, such as email subscriptions and view-only usage, Power BI empowers users to explore and interact with reports and datasets. The responsiveness of visuals for this self-service workload is largely driven by fundamental data model design decisions, as explained in the following subsections.

Additional performance factors outside the scope of this chapter include the hardware resources allocated to the dataset, such as with Power BI Premium capacities (v-cores, RAM), the efficiency of the DAX measures created for the dataset, the design of the Power BI reports that query the dataset, and the volume and timing of queries generated by users.

We first take a look at optimizing import mode datasets.

Import

The performance of an...

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