Course Outline
Module 1: Get data in Power BI
In this module, you will learn how to retrieve data from a variety of sources, including Microsoft Excel, relational databases, and NoSQL data stores. You will also discover methods to improve performance during data retrieval.
Learning objectives
By the end of this module, you will be able to:
- Identify and connect to a data source
- Get data from a relational database, such as Microsoft SQL Server
- Get data from a file, like Microsoft Excel
- Get data from applications
- Get data from Azure Analysis Services
- Select a storage mode
- Fix performance issues
- Resolve data import errors
Lessons
- Introduction
- 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
- Exercise - Prepare data in Power BI Desktop
- Check your knowledge
- Summary
Module 2: Clean, transform, and load data in Power BI
This module teaches you how to simplify complex models, change data types, rename objects, and pivot data. You will also learn how to profile columns to identify valuable data for deeper analytics.
Learning objectives
By the end of this module, you will be able to:
- Resolve inconsistencies, unexpected or null values, and data quality issues.
- Apply user-friendly value replacements.
- Profile data to gain insights into specific columns before usage.
- Evaluate and transform column data types.
- Apply data shape transformations to table structures.
- Combine queries.
- Apply user-friendly naming conventions to columns and queries.
- Edit M code in the Advanced Editor.
Lessons
- Introduction
- 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
- Exercise - Load data in Power BI Desktop
- Check your knowledge
- Summary
Module 3: Design a data model in Power BI
Creating a complex data model in Power BI is straightforward. When data originates from multiple transactional systems, you may end up with dozens of tables. Building an effective data model involves simplifying this complexity. A star schema is one method to achieve this, and this module covers the terminology and implementation. You will also understand why selecting the correct data granularity is crucial for the performance and usability of your Power BI reports. Finally, you will learn techniques to improve performance within your Power BI data models.
Learning objectives
In this module, you will:
- Create common date tables
- Configure many-to-many relationships
- Resolve circular relationships
- Design star schemas
Lessons
- Introduction
- Work with tables
- Create a date table
- Work with dimensions
- Define data granularity
- Work with relationships and cardinality
- Resolve modeling challenges
- Exercise - Model data in Power BI Desktop
- Check your knowledge
- Summary
Module 4: Design Power BI reports
With Power BI offering more than 30 core visuals, selecting the appropriate one can be challenging for beginners. This module guides you through choosing the most suitable visual type to meet your design and report layout requirements.
Learning objectives
In this module, you will:
- Learn about the structure of a Power BI report.
- Learn about report objects.
- Select the appropriate visual type to use.
Lessons
- Introduction
- 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
- Exercise - Design a report in Power BI desktop
- Check your knowledge
- Summary
Module 5: Configure Power BI report filters
Report filtering is a complex topic due to the numerous techniques available for filtering a Microsoft Power BI report. However, complexity brings control, allowing you to design reports that meet specific requirements and expectations. Some filtering techniques apply at design time, while others are relevant during report consumption (in reading view). What matters most is that your report design enables consumers to intuitively narrow down to the data points that interest them.
Learning objectives
In this module, you will:
- Design reports for filtering.
- Design reports with slicers.
- Design reports using advanced filtering techniques.
- Apply consumption-time filtering.
- Select appropriate report filtering techniques.
Lessons
- Introduction to designing reports for filtering
- 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
- Summary
Module 6: Create dashboards in Power BI
Microsoft Power BI dashboards differ from Power BI reports. Dashboards allow consumers to create a single, personalized artifact of directed data. Dashboards can be composed of pinned visuals taken from different reports. While a Power BI report uses data from a single dataset, a Power BI dashboard can contain visuals from multiple datasets.
Learning objectives
In this module, you will:
- Set a mobile view.
- Add a theme to the visuals in your dashboard.
- Configure data classification.
- Add real-time dataset visuals to your dashboards.
- Pin a live report page to a dashboard.
Lessons
- 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
- Exercise - Create a Power BI dashboard
- Check your knowledge
- Summary
Requirements
N/A
Testimonials (1)
engagement with the attendees
