Contents

Introduction

Organization of this book

Preparing for the exam

Microsoft certifications

Companion files

Quick access to online references

Errata, updates, & book support

Stay in touch

Chapter 1 Prepare the data

Skill 1.1: Get data from different data sources

Identify and connect to a data source

Change data source settings

Select a shared dataset or create a local dataset

Select a storage mode

Choose an appropriate query type

Identify query performance issues

Use Microsoft Dataverse

Use parameters

Use or create a PBIDS file

Use or create a dataflow

Connect to a dataset by using the XMLA endpoint

Skill 1.2: Profile the data

Identify data anomalies

Examine data structures and interrogate column properties

Interrogate data statistics

Skill 1.3: Clean, transform, and load the data

Resolve inconsistencies, unexpected or null values, and data quality issues and apply user-friendly value replacements

Evaluate and transform column data types

Identify and create appropriate keys for joins

Apply data shape transformations to table structures

Combine queries

Apply user-friendly naming conventions to columns and queries

Leverage the Advanced Editor to modify Power Query M code

Configure data loading

Resolve data import errors

Chapter summary

Thought experiment

Thought experiment answers

Chapter 2 Model the data

Skill 2.1: Design a data model

Define the tables

Configure table and column properties

Define quick measures

Flatten out a parent-child hierarchy

Define role-playing dimensions

Define a relationship’s cardinality and cross-filter direction

Design the data model to meet performance requirements

Resolve many-to-many relationships

Create a common date table

Define the appropriate level of data granularity

Skill 2.2: Develop a data model

Apply cross-filter direction and security filtering

Create calculated tables

Create hierarchies

Create calculated columns

Implement row-level security roles

Set up the Q&A feature

Skill 2.3: Create measures by using DAX

Use DAX to build complex measures

Use CALCULATE to manipulate filters

Implement Time Intelligence using DAX

Replace numeric columns with measures

Use basic statistical functions to enhance data

Create semi-additive measures

Skill 2.4: Optimize model performance

Remove unnecessary rows and columns

Identify poorly performing measures, relationships, and visuals

Improve cardinality levels by changing data types

Improve cardinality levels through summarization

Create and manage aggregations

Chapter summary

Thought experiment

Thought experiment answers

Chapter 3 Visualize the data

Skill 3.1: Create reports

Add visualization items to reports

Choose an appropriate visualization type

Format and configure visualizations

Import a custom visual

Configure conditional formatting

Apply slicing and filtering

Add an R or Python visual

Configure the report page

Design and configure for accessibility

Configure automatic page refresh

Create a paginated report

Skill 3.2: Create dashboards

Manage tiles on a dashboard

Set mobile view

Configure data alerts

Use the Q&A feature

Add a dashboard theme

Pin a live report page to a dashboard

Skill 3.3: Enrich reports for usability

Configure bookmarks

Create custom tooltips

Edit and configure interactions between visuals

Configure navigation for a report

Apply sorting

Configure Sync slicers

Use the Selection pane

Use drill-through and cross-filter

Drill down into data using interactive visuals

Export report data

Design reports for mobile devices

Chapter summary

Thought experiment

Thought experiment answers

Chapter 4 Analyze the data

Skill 4.1: Enhance reports to expose insights

Apply conditional formatting

Perform top N analysis

Explore statistical summary

Add a Quick Insights result to a dashboard

Create reference lines by using the Analytics pane

Use the Play Axis feature of a visualization and conduct time-series analysis

Personalize visuals

Skill 4.2: Perform advanced analysis

Identify outliers

Use groupings and binnings

Use the Key influencers to explore dimensional variances

Use the Decomposition tree visual to break down a measure

Apply AI Insights

Chapter summary

Thought experiment

Thought experiment answers

Chapter 5 Deploy and maintain deliverables

Skill 5.1: Manage datasets

Configure a dataset scheduled refresh

Configure row-level security group membership

Provide access to datasets

Configure incremental refresh settings

Promote or certify Power BI content

Configure large dataset format

Skill 5.2: Create and manage workspaces

Create and configure a workspace

Recommend a development lifecycle strategy

Assign workspace roles

Configure and update a workspace app

Publish, import, or update assets in a workspace

Apply sensitivity labels to workspace content

Configure subscriptions

Chapter summary

Thought experiment

Thought experiment answers

Index

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