Duration: 5 days – 35 hrs
Overview
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.
Objectives
• Understand the key features and components of Power BI.
• Learn how to navigate the Power BI interface and workspace.
• Connect to various data sources (e.g., Excel, databases, web services).
• Clean, transform, and load data using Power Query Editor.
• Create and manage relationships between different data tables.
• Understand and implement data modeling best practices.
• Learn the basics of DAX for creating calculated columns and measures.
• Use DAX functions to perform complex calculations.
• Create and customize interactive reports and dashboards.
• Use various visualizations (e.g., charts, maps, tables) to present data effectively.
• Implement advanced analytics features such as Quick Insights and AI visuals.
• Perform time-series analysis and predictive analytics.
• Publish reports to the Power BI Service.
• Share dashboards and reports with stakeholders and collaborate in real-time.
• Understand Power BI administration and security settings.
• Manage data gateways and data refresh schedules.
• Learn best practices for designing efficient Power BI solutions.
• Optimize data models and report performance.
Audience
Data Analysts and Business Analysts:
• Professionals who analyze data to provide insights for decision-making.
• Those who need to create interactive reports and dashboards.
Business Intelligence Professionals:
• Individuals involved in designing, developing, and maintaining BI solutions.
• Those responsible for data modeling and visualization in their organizations.
Data Scientists and Data Engineers:
• Professionals who work with large datasets and need to perform data analysis and visualization tasks.
• Those looking to enhance their skills in data visualization and reporting.
IT Professionals:
• System administrators and IT managers who support Power BI implementations.
• Those responsible for managing data sources and security in Power BI.
Financial Analysts and Marketing Analysts:
• Analysts who analyze financial or marketing data to derive insights and make data-driven decisions.
• Those who need to create compelling visualizations to communicate findings.
Project Managers and Consultants:
• Professionals who oversee projects and need to track key performance indicators (KPIs) using interactive dashboards.
• Consultants who provide data analysis and reporting services to clients.
Students and Aspiring Data Professionals:
• Individuals looking to start a career in data analysis or business intelligence.
• Students studying data science, analytics, or related fields who want to gain practical skills in Power BI.
Prerequisites
• Basic understanding of data analysis concepts.
• Familiarity with Microsoft Excel and data visualization principles is beneficial but not required.
Course Content
Discover data analysis
• Overview of data analysis
• Roles in data
• Tasks of a data analyst
Get started building with Power BI
• Use Power BI
• Building blocks of Power BI
• Tour and use the Power BI service
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
Design a semantic model in Power BI
• Create a date table
• Work with dimensions
• Define data granularity
• Work with relationships and cardinality
• Resolve modeling challenges
Add measures to Power BI models
• Create simple measures
• Create compound measures
• Create quick measures
• Compare calculated columns with measures
Add calculated tables and columns to Power BI Desktop models
• Create calculated columns
• Learn about row context
• Choose a technique to add a column
Use DAX time intelligence functions in Power BI Desktop models
• Use DAX time intelligence functions
• Additional time intelligence calculations
Optimize a model for performance in Power BI
• Introduction to performance optimization
• 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
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
Configure Power BI report filters
• 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
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 with built-in assistance
• Tune report performance
• Optimize reports for mobile use
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 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
Manage semantic models in Power BI
• Use a Power BI gateway to connect to on-premises data sources
• Configure a semantic model scheduled refresh
• Configure incremental refresh settings
• Manage and promote semantic models
• Troubleshoot service connectivity
• Boost performance with query caching
Create dashboards in Power BI
• Introduction to dashboards
• Configure data alerts
• Explore data by asking questions
Implement row-level security
• Configure row-level security with the static method
• Configure row-level security with the dynamic method
