Course Outline
Module 1: Ingesting Data in Power BI
In this module, you will learn how to retrieve data from a wide range of sources, including Microsoft Excel, relational databases, and NoSQL data stores. You will also discover methods to optimize performance during data retrieval.
Learning objectives
By the end of this module, you will be able to:
- Identify and connect to a data source
- Retrieve data from a relational database, such as Microsoft SQL Server
- Retrieve data from files, such as Microsoft Excel
- Retrieve data from applications
- Retrieve data from Azure Analysis Services
- Select an appropriate storage mode
- Troubleshoot performance issues
- Resolve data import errors
Lessons
- Introduction
- Retrieve data from files
- Retrieve data from relational data sources
- Create dynamic reports using parameters
- Retrieve data from a NoSQL database
- Retrieve data from online services
- Select a storage mode
- Retrieve data from Azure Analysis Services
- Troubleshoot performance issues
- Resolve data import errors
- Exercise - Prepare data in Power BI Desktop
- Assess your knowledge
- Summary
Module 2: Cleaning, Transforming, and Loading 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 needed 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 understand specific columns better before using them.
- 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 the Advanced Editor to modify M code
- Exercise - Load data in Power BI Desktop
- Assess your knowledge
- Summary
Module 3: Designing a Data Model in Power BI
Creating a complex data model in Power BI is a straightforward process. If your data originates from multiple transactional systems, you may quickly find yourself working with dozens of tables. Building an effective data model involves simplifying this complexity. A star schema is one method for simplifying a data model, and you will learn the terminology and implementation details in this module. You will also understand why choosing the correct data granularity is crucial for the performance and usability of your Power BI reports. Finally, you will learn how 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
- Assess your knowledge
- Summary
Module 4: Designing Power BI Reports
Since Power BI includes over 30 core visuals, it can be challenging for beginners to select the correct visual. This module will guide you through choosing the most appropriate 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
- Assess your knowledge
- Summary
Module 5: Configuring Power BI Report Filters
Report filtering is a complex topic because many techniques are available for filtering a Microsoft Power BI report. However, with complexity comes control, allowing you to design reports that meet requirements and expectations. Some filtering techniques apply at design time, while others are relevant at report consumption time (in reading view). What matters is that your report design allows 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
- Assess your knowledge
- Summary
Module 6: Creating 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
- Assess your knowledge
- Summary
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