Exam DA-100 Analyzing Data with Microsoft Power BI (Video)

Exam DA-100 Analyzing Data with Microsoft Power BI (Video)

by Chris Sorensen
Released October 2021
Publisher(s): Microsoft Press
ISBN: 0137574525

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Video description

8+ Hours of Video Instruction

Prepare for Microsoft Exam DA-100 and demonstrate your mastery of Power BI data analysis and visualization.

This Exam DA-100: Analyzing Data with Microsoft Power BI video is designed for data analysts responsible for designing scalable data models, cleaning and transforming data, and presenting analytic insights through data visualizations using Power BI. This video focuses on the skills measured by the exam objectives, as updated by Microsoft on July 29, 2021.
  • Prepare the data
  • Model the data
  • Visualize the data
  • Analyze the data
  • Deploy and maintain deliverables
Using his years of experience teaching Power BI to a variety of learners, Microsoft Certified Trainer Chris Sorensen explains how to optimize Power BI features and functions and prepares you for what to expect on the DA-100 exam. In his engaging style grounded in real-world scenarios, Chris gives you insights to navigate and build effective Power BI solutions, quickly and effectively. With Chris as your guide, you are well-equipped to advance in your career as a data analyst.

About the Instructor

Chris Sorensen, CPA, CGA, is the Founder and President of Iteration Insights, a tech-enabled data analytics solutions provider based in Calgary, Alberta. He is a Microsoft Certified Data Analyst Associate and Microsoft Certified Trainer with a combined 20+ years of industry and teaching experience. In his career, he has led numerous Analytics projects in more than 15 industries across small to enterprise-sized organizations.

As an adjunct instructor of the Business Intelligence program at SAIT, he plays a significant role in shaping new talent in Calgary’s emerging tech sector. Following his lifelong learning approach, Chris also coordinates both Power Platform and Azure Analytics User Groups, providing a space dedicated to knowledge-sharing and growing Alberta’s tech community. His favorite hashtag is #neverstoplearning.

Skill Level
  • Intermediate
Who Should Take This Course
  • Certification candidates preparing for Exam DA-100: Analyzing Data with Microsoft Power BI
  • Data analysts who want to use Microsoft Power BI to maximize their data assets
  • Business intelligence professionals who want to advance their knowledge of data processing and analytics
Course Requirements
  • Power BI Desktop installed on your machine
  • Access to the Power BI service
  • Familiarity with the end-to-end process of connecting to data sources, cleaning and transforming data, modeling data for self-service consumption, building reports, and securely distributing reports and dashboards

Table of contents

  1. Introduction
    1. Exam DA-100: Analyzing Data with Microsoft Power BI: Introduction
  2. Module 1: Prepare the Data
    1. Module introduction
  3. Lesson 1: Get Data from Different Data Sources
    1. Learning objectives
    2. 1.1 Identify and connect to a data source
    3. 1.2 Change data source settings
    4. 1.3 Select a shared dataset or create a local dataset
    5. 1.4 Select a storage mode
    6. 1.5 Choose an appropriate query type
    7. 1.6 Identify query performance issues
    8. 1.7 Use Microsoft Dataverse
    9. 1.8 Use parameters
    10. 1.9 Use or create a PBIDS file
    11. 1.10 Use or create a data flow
    12. 1.11 Connect to a dataset using the XMLA endpoint
  4. Lesson 2: Profile the Data
    1. Learning objectives
    2. 2.1 Identify data anomalies
    3. 2.2 Examine data structures
    4. 2.3 Interrogate column properties
    5. 2.4 Interrogate data statistics
  5. Lesson 3: Clean, Transform, and Load the Data
    1. Learning objectives
    2. 3.1 Resolve inconsistencies, unexpected or null values, and data quality issues
    3. 3.2 Apply user-friendly value replacements
    4. 3.3 Identify and create appropriate keys for joins
    5. 3.4 Evaluate and transform column data types
    6. 3.5 Apply data shape transformations to table structures
    7. 3.6 Combine queries
    8. 3.7 Apply user-friendly naming conventions to columns and queries
    9. 3.8 Leverage Advanced Editor to modify Power Query M code
    10. 3.9 Configure data loading
    11. 3.10 Resolve data import errors
  6. Module 2: Model the Data
    1. Module introduction
  7. Lesson 4: Design a Data Model
    1. Learning objectives
    2. 4.1 Define the tables
    3. 4.2 Configure table and column properties
    4. 4.3 Define quick measures
    5. 4.4 Flatten out a parent-child hierarchy
    6. 4.5 Define role-playing dimensions
    7. 4.6 Define a relationship's cardinality and cross-filter direction
    8. 4.7 Design the data model to meet performance requirements
    9. 4.8 Resolve many-to-many relationships
    10. 4.9 Create a common date table
    11. 4.10 Define the appropriate level of data granularity
    12. 4.11 Apply or change sensitivity labels
  8. Lesson 5: Develop a Data Model
    1. Learning objectives
    2. 5.1 Apply cross-filter direction and security filtering
    3. 5.2 Create calculated tables
    4. 5.3 Create hierarchies
    5. 5.4 Create calculated columns
    6. 5.5 Implement row-level security roles
    7. 5.6 Set up the Q feature
    8. 5.7 Implement object-level security
  9. Lesson 6: Create Measures by Using DAX
    1. Learning objectives
    2. 6.1 Use DAX to build complex measures
    3. 6.2 Use CALCULATE to manipulate filters
    4. 6.3 Implement Time Intelligence using DAX
    5. 6.4 Replace numeric columns with measures
    6. 6.5 Use basic statistical functions to enhance data
    7. 6.6 Create semi-additive measures
  10. Lesson 7: Optimize Model Performance
    1. Learning objectives
    2. 7.1 Remove unnecessary rows and columns
    3. 7.2 Identify poorly performing measures, relationships, and visuals
    4. 7.3 Improve cardinality levels
    5. 7.4 Optimize DirectQuery models
    6. 7.5 Create and manage aggregations
    7. 7.6 Use Query Diagnostics
  11. Module 3: Visualize the Data
    1. Module introduction
  12. Lesson 8: Create Reports
    1. Learning objectives
    2. 8.1 Add visualization items to reports
    3. 8.2 Choose an appropriate visualization type
    4. 8.3 Format and configure visualizations
    5. 8.4 Import a custom visual
    6. 8.5 Configure and apply conditional formatting
    7. 8.6 Apply slicing and filtering
    8. 8.7 Add an R or Python visual
    9. 8.8 Configure the report page
    10. 8.9 Design and configure for accessibility
    11. 8.10 Configure automatic page refresh
    12. 8.11 Create a paginated report
    13. 8.12 Add a Smart Narrative visual
  13. Lesson 9: Create Dashboards
    1. Learning objectives
    2. 9.1 Build a dashboard
    3. 9.2 Set mobile view
    4. 9.3 Manage tiles on a dashboard
    5. 9.4 Configure data alerts
    6. 9.5 Use the Q feature
    7. 9.6 Add a dashboard theme
    8. 9.7 Pin a live report page to a dashboard
  14. Lesson 10: Enrich Reports for Usability
    1. Learning objectives
    2. 10.1 Configure bookmarks
    3. 10.2 Create custom tooltips
    4. 10.3 Edit and configure interactions between visuals
    5. 10.4 Configure navigation for a report
    6. 10.5 Apply sorting
    7. 10.6 Configure Sync Slicers
    8. 10.7 Use the selection pane
    9. 10.8 Use drillthrough and cross filter
    10. 10.9 Drilldown into data using interactive visuals
    11. 10.10 Export report data
    12. 10.11 Design reports for mobile devices
  15. Module 4: Analyze the Data
    1. Module introduction
  16. Lesson 11: Enhance Reports to Expose Insights
    1. Learning objectives
    2. 11.1 Perform top N analysis
    3. 11.2 Explore statistical summary
    4. 11.3 Use the Q visual
    5. 11.4 Add a Quick Insights result to a report
    6. 11.5 Create reference lines by using Analytics pane
    7. 11.6 Personalize visuals
  17. Lesson 12: Perform Advanced Analysis
    1. Learning objectives
    2. 12.1 Identify outliers
    3. 12.2 Conduct Time Series analysis
    4. 12.3 Use groupings and binnings
    5. 12.4 Use the Key Influencers to explore dimensional variances
    6. 12.5 Use the decomposition tree visual to break down a measure
    7. 12.6 Apply AI Insights
    8. 12.7 Use anomaly detection
  18. Module 5: Deploy and Maintain Deliverables
    1. Module introduction
  19. Lesson 13: Manage Datasets
    1. Learning objectives
    2. 13.1 Configure a dataset scheduled refresh
    3. 13.2 Configure row-level security group membership
    4. 13.3 Provide access to datasets
    5. 13.4 Configure incremental refresh settings
    6. 13.5 Promote or certify Power BI datasets
    7. 13.6 Identify downstream dataset dependencies
    8. 13.7 Configure large dataset format
  20. Lesson 14: Create and Manage Workspaces
    1. Learning objectives
    2. 14.1 Create and configure a workspace
    3. 14.2 Recommend a development lifecycle strategy
    4. 14.3 Assign workspace roles
    5. 14.4 Configure and update a workspace app
    6. 14.5 Publish, import, or update assets in a workspace
    7. 14.6 Apply sensitivity labels to workspace content
    8. 14.7 Use deployment pipelines
    9. 14.8 Configure subscriptions
    10. 14.9 Promote or certify Power BI content
  21. Summary
    1. Exam DA-100: Analyzing Data with Microsoft Power BI: Summary

Product information

  • Title: Exam DA-100 Analyzing Data with Microsoft Power BI (Video)
  • Author(s): Chris Sorensen
  • Release date: October 2021
  • Publisher(s): Microsoft Press
  • ISBN: 0137574525