This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.

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* Actual course outline may vary depending on offering center. Contact your sales representative for more information.

Learning Objectives

With this course completion, students will:
Learn how Power BI services and applications work together
Explore how Power BI can make your business more efficient
Learn how to create compelling visuals and reports
Get date from external sources
Fix performance issues
Resolve data import errors
Apply data shape transformations to table structures
Combine queries
Create common date tables
Configure many-to-many relationships
Resolve circular relationships
Design star schemas
Describe similarities of, and differences between, a calculated column and a measure
Add a date table to your model by using DAX calculations
Optimize DirectQuery models with table level storage.
Design reports
Perform analytics
Create dashboards
Implement row-level security

1

  • MODULE 1: DISCOVER DATA ANALYTICS

    • Overview of data analysis
    • Roles in data
    • Tasks of a data analyst
2

  • MODULE 2: GET STARTED BUILDING WITH POWER BI

    • Use Power BI
    • Building blocks of Power BI
    • Tour and use the Power BI service
3

  • MODULE 3: GET DATA IN POWER BI

    • Get data from files
    • Get data from relational data sources
    • Create dynamic reports with parameters
    • Get data from a NoSQL database
    • Get data from online services
    • Select a storage mode
    • Get data from Azure Analysis Services
    • Fix performance issues
    • Resolve data import errors
4

  • MODULE 4: CLEAN, TRANSFORM, AND LOAD DATA IN POWER BI

    • Shape the initial data
    • Simplify the data structure
    • Evaluate and change column data types
    • Combine multiple tables into a single table
    • Profile data in Power BI
    • Use Advanced Editor to modify M code
5

  • MODULE 5: DESIGN A DATA MODEL IN POWER BI

    • Work with tables
    • Create a date table
    • Work with dimensions
    • Define data granularity
    • Work with relationships and cardinality
    • Resolve modeling challenges
6

  • MODULE 6: ADD MEASURES TO POWER BI DESKTOP MODELS

    • Create simple measures
    • Create compound measures
    • Create quick measures
    • Compare calculated columns with measures
7

  • MODULE 7: ADD CALCULATED TABLES AND COLUMNS TO POWER BI DESKTOP MODELS

    • Create calculated columns
    • Learn about row context
    • Choose a technique to add a column
8

  • MODULE 8:USE DAX TIME INTELLIGENCE FUNCTIONS IN POWER BI DESKTOP MODELS

    • Use DAX time intelligence functions
    • Additional time intelligence calculations
9

  • MODULE 9: OPTIMIZE A MODEL FOR PERFORMANCE IN POWER BI

    • Review performance of measures, relationships, and visuals
    • Use variables to improve performance and troubleshooting
    • Reduce cardinality
    • Optimize DirectQuery models with table level storage
    • Create and manage aggregations
10

  • MODULE 10: DESIGN POWER BI REPORTS

    • Design the analytical report layout
    • Design visually appealing reports
    • Report objects
    • Select report visuals
    • Select report visuals to suit the report layout
    • Format and configure visualizations
    • Work with key performance indicators
11

  • MODULE 11: CONFIGURE POWER BI REPORT FILTERS

    • Apply filters to the report structure
    • Apply filters with slicers
    • Design reports with advanced filtering techniques
    • Consumption-time filtering
    • Select report filter techniques
    • Case study - Configure report filters based on feedback
12

  • MODULE 12: ENHANCE POWER BI REPORT DESIGNS FOR THE USER EXPERIENCE

    • Design reports to show details
    • Design reports to highlight values
    • Design reports that behave like apps
    • Work with bookmarks
    • Design reports for navigation
    • Work with visual headers
    • Design reports with built-in assistance
    • Tune report performance
    • Optimize reports for mobile use
13

  • MODULE 13: PERFORM ANALYTICS IN POWER BI

    • Introduction to analytics
    • Explore statistical summary
    • Identify outliers with Power BI visuals
    • Group and bin data for analysis
    • Apply clustering techniques
    • Conduct time series analysis
    • Use the Analyze feature
    • Create what-if parameters
    • Use specialized visuals
14

  • MODULE 14: CREATE AND MANAGE WORKSPACES IN POWER BI

    • Distribute a report or dashboard
    • Monitor usage and performance
    • Recommend a development life cycle strategy
    • Troubleshoot data by viewing its lineage
    • Configure data protection
15

  • MODULE 15: MANAGE DATASETS IN POWER BI

    • Use a Power BI gateway to connect to on-premises data sources
    • Configure a dataset scheduled refresh
    • Configure incremental refresh settings
    • Manage and promote datasets
    • Troubleshoot service connectivity
    • Boost performance with query caching (Premium)
16

  • MODULE 16: CREATE DASHBOARDS IN POWER BI

    • Introduction to dashboards
    • Configure data alerts
    • Explore data by asking questions
    • Review Quick insights
    • Add a dashboard theme
    • Pin a live report page to a dashboard
    • Configure a real-time dashboard
    • Configure data classification
    • Set mobile view
17

  • MODULE 17: IMPLEMENT ROW-LEVEL SECURITY

    • Configure row-level security with the static method
    • Configure row-level security with the dynamic method

Audience

The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.

Language

English

Prerequisites

Prior to taking this course, students should have: - Understanding of core data concepts. - Knowledge of working with relational data in the cloud. - Knowledge of working with non-relational data in the cloud. - Knowledge of data analysis and visualization concepts. You can gain the prerequisites and a better understanding of working with data in Azure by completing the course Microsoft Azure Data Fundamentals before taking this course.

$1,785

Length: 3.0 days (24 hours)

Level:

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