Introduction to Microsoft Power BI Data Analyst Training
Introduction to Microsoft Power BI Data Analyst (PL-300)
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.
Training at a glance
Level
Beginner
Duration
3 Days
Experience
1 year: Core Data Concepts
Average Salary
$82,640
Labs
Yes
Level
Beginner
Duration
3 Days
Experience
0 year: Core Data Concepts
Average Salary
$82,640
Labs
Yes
Training Details
This course will discuss 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 also show how to access and process data from a range of data sources including both relational and non-relational data. This course will explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will discuss how to manage and deploy reports and dashboards for sharing and content distribution. Finally, this course will show how to build paginated reports within the Power BI service and publish them to a workspace for inclusion within Power BI.
1 - Discover data analysis
- Overview of data analysis
- Roles in data
- Tasks of a data analyst
- Check your knowledge
2 - Get started building with Power BI
- Use Power BI
- Building blocks of Power BI
- Tour and use the Power BI service
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
- Check your knowledge
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
- Check your knowledge
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
- Check your knowledge
6 - Add measures to Power BI Desktop models
- Create simple measures
- Create compound measures
- Create quick measures
- Compare calculated columns with measures
- Check your knowledge
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
- Check your knowledge
8 - Use DAX time intelligence functions in Power BI Desktop models
- Use DAX time intelligence functions
- Additional time intelligence calculations
- Check your knowledge
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
- Check your knowledge
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
- Check your knowledge
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
- Check your knowledge
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
- Check your knowledge
13 - Perform analytics in Power BI
- 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
- Check your knowledge
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
- Check your knowledge
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)
- Check your knowledge
16 - Create dashboards in Power BI
- 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
- Check your knowledge
17 - Implement row-level security
- Configure row-level security with the static method
- Configure row-level security with the dynamic method
- Check your knowledge
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.
- Understanding 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
- DP-900 Microsoft Azure Data Fundamentals is recommended
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