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E-raamat: Exam Ref DA-100 Analyzing Data with Microsoft Power BI

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  • Formaat: 288 pages
  • Sari: Exam Ref
  • Ilmumisaeg: 27-Apr-2021
  • Kirjastus: Addison Wesley
  • Keel: eng
  • ISBN-13: 9780136819615
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Exam Ref DA-100 Analyzing Data with Microsoft Power BISuurem pilt
  • Formaat: 288 pages
  • Sari: Exam Ref
  • Ilmumisaeg: 27-Apr-2021
  • Kirjastus: Addison Wesley
  • Keel: eng
  • ISBN-13: 9780136819615
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Direct from Microsoft, this Exam Ref is the official study guide for the new Microsoft DA-100 Analyzing Data with Microsoft Power BI certification exam.


Exam Ref DA-100 Analyzing Data with Microsoft Power BI offers professional-level preparation that helps candidates maximize their exam performance and sharpen their skills on the job. It focuses on specific areas of expertise modern IT professionals need to demonstrate real-world mastery of Power BI data analysis and visualization. Coverage includes:

  • Preparing data: acquiring, profiling, cleaning, transforming, and loading data
  • Modeling data: designing and developing data models, creating measures with DAX, and optimizing model performance
  • Visualizing data: creating reports and dashboards, and enriching reports for usability
  • Analyzing data: enhancing reports to expose insights, and performing advanced analysis
  • Deploying and maintaining deliverables: managing datasets; creating and managing workspaces


Microsoft Exam Ref publications stand apart from third-party study guides because they:

  • Provide guidance from Microsoft, the creator of Microsoft certification exams
  • Target IT professional-level exam candidates with content focused on their needs, not “one-size-fits-all” content
  • Streamline study by organizing material according to the exam’s objective domain (OD), covering one functional group and its objectives in each chapter
  • Feature Thought Experiments to guide candidates through a set of “what if?” scenarios, and prepare them more effectively for Pro-level style exam questions
  • Explore big picture thinking around the planning and design aspects of the IT pro’s job role


For more information on Exam DA-100 and the Microsoft Certified: Data Analyst Associate credential, visit https://docs.microsoft.com/en-us/learn/certifications/data-analyst-associate.

Introduction xiv
Organization of this book xiv
Preparing for the exam xiv
Microsoft certifications xv
Companion files xv
Quick access to online references xvi
Errata, updates, & book support xvi
Stay in touch xvi
Chapter 1 Prepare the data
1(66)
Skill 1.1 Get data from different data sources
1(26)
Identify and connect to a data source
2(4)
Change data source settings
6(1)
Select a shared dataset or create a local dataset
7(2)
Select a storage mode
9(3)
Choose an appropriate query type
12(3)
Identify query performance issues
15(3)
Use Microsoft Dataverse
18(1)
Use parameters
19(5)
Use or create a PBIDS file
24(1)
Use or create a dataflow
25(1)
Connect to a dataset by using the XMLA endpoint
26(1)
Skill 1.2 Profile the data
27(4)
Identify data anomalies
27(1)
Examine data structures and interrogate column properties
28(2)
Interrogate data statistics
30(1)
Skill 1.3 Clean, transform, and load the data
31(36)
Resolve inconsistencies, unexpected or null values, and data quality issues and apply user-friendly value replacements
32(3)
Evaluate and transform column data types
35(3)
Identify and create appropriate keys for joins
38(2)
Apply data shape transformations to table structures
40(10)
Combine queries
50(5)
Apply user-friendly naming conventions to columns and queries
55(1)
Leverage the Advanced Editor to modify Power Query code
55(3)
Configure data loading
58(1)
Resolve data import errors
59(2)
Chapter summary
61(1)
Thought experiment
62(2)
Thought experiment answers
64(3)
Chapter 2 Model the data
67(74)
Skill 2.1 Design a data model
67(29)
Define the tables
68(3)
Configure table and column properties
71(2)
Define quick measures
73(3)
Flatten out a parent-child hierarchy
76(3)
Define role-playing dimensions
79(3)
Define a relationship's cardinality and cross-filter direction
82(4)
Design the data model to meet performance requirements
86(1)
Resolve many-to-many relationships
87(4)
Create a common date table
91(3)
Define the appropriate level of data granularity
94(2)
Skill 2.2 Develop a data model
96(17)
Apply cross-filter direction and security filtering
97(1)
Create calculated tables
97(2)
Create hierarchies
99(1)
Create calculated columns
100(2)
Implement row-level security roles
102(6)
Set up the Q&A feature
108(5)
Skill 2.3 Create measures by using DAX
113(15)
Use DAX to build complex measures
113(3)
Use CALCULATE to manipulate filters
116(6)
Implement Time Intelligence using DAX
122(2)
Replace numeric columns with measures
124(1)
Use basic statistical functions to enhance data
125(1)
Create semi-additive measures
125(3)
Skill 2.4 Optimize model performance
128(13)
Remove unnecessary rows and columns
128(1)
Identify poorly performing measures, relationships, and visuals
129(1)
Improve cardinality levels by changing data types
130(1)
Improve cardinality levels through summarization
131(1)
Create and manage aggregations
131(2)
Chapter summary
133(2)
Thought experiment
135(3)
Thought experiment answers
138(3)
Chapter 3 Visualize the data
141(60)
Skill 3.1 Create reports
141(31)
Add visualization items to reports
142(1)
Choose an appropriate visualization type
143(11)
Format and configure visualizations
154(1)
Import a custom visual
155(1)
Configure conditional formatting
156(2)
Apply slicing and filtering
158(3)
Add an R or Python visual
161(3)
Configure the report page
164(1)
Design and configure for accessibility
165(3)
Configure automatic page refresh
168(2)
Create a paginated report
170(2)
Skill 3.2 Create dashboards
172(8)
Manage tiles on a dashboard
172(2)
Set mobile view
174(2)
Configure data alerts
176(1)
Use the Q&A feature
177(1)
Add a dashboard theme
178(1)
Pin a live report page to a dashboard
179(1)
Skill 3.3 Enrich reports for usability
180(21)
Configure bookmarks
180(3)
Create custom tooltips
183(2)
Edit and configure interactions between visuals
185(1)
Configure navigation for a report
186(1)
Apply sorting
187(1)
Configure Sync slicers
188(2)
Use the Selection pane
190(1)
Use drill-through and cross-filter
191(2)
Drill down into data using interactive visuals
193(1)
Export report data
194(1)
Design reports for mobile devices
195(1)
Chapter summary
196(2)
Thought experiment
198(1)
Thought experiment answers
199(2)
Chapter 4 Analyze the data
201(28)
Skill 4.1 Enhance reports to expose insights
201(14)
Apply conditional formatting
202(4)
Perform top N analysis
206(2)
Explore statistical summary
208(2)
Add a Quick Insights result to a dashboard
210(1)
Create reference lines by using the Analytics pane
211(1)
Use the Play Axis feature of a visualization and conduct time-series analysis
212(2)
Personalize visuals
214(1)
Skill 4.2 Perform advanced analysis
215(14)
Identify outliers
215(2)
Use groupings and binnings
217(2)
Use the Key influencers to explore dimensional variances
219(3)
Use the Decomposition tree visual to break down a measure
222(1)
Apply Al Insights
223(1)
Chapter summary
224(1)
Thought experiment
225(2)
Thought experiment answers
227(2)
Chapter 5 Deploy and maintain deliverables
229(30)
Skill 5.1 Manage datasets
229(17)
Configure a dataset scheduled refresh
230(2)
Configure row-level security group membership
232(3)
Provide access to datasets
235(3)
Configure incremental refresh settings
238(4)
Promote or certify Power Bl content
242(2)
Configure large dataset format
244(2)
Skill 5.2 Create and manage workspaces
246(13)
Create and configure a workspace
246(2)
Recommend a development lifecycle strategy
248(2)
Assign workspace roles
250(1)
Configure and update a workspace app
251(4)
Publish, import, or update assets in a workspace
255(1)
Apply sensitivity labels to workspace content
256(1)
Configure subscriptions
257(2)
Chapter summary 259(2)
Thought experiment 261(1)
Thought experiment answers 262(1)
Index 263
DANIIL MASLYUK is an independent business intelligence consultant, trainer, and speaker who specializes in Microsoft Power BI. Daniil blogs at xxlbi.com and tweets as @DMaslyuk.
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