Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Data Acquisition and Transformation
Introduction to Power BI
-
Power BI Ecosystem
- Power BI Desktop – the primary authoring tool for creating reports and data models
- Power BI Service – cloud platform for publishing, sharing, and collaboration
- Power BI Mobile – accessing reports and dashboards on iOS and Android devices
-
Power BI Desktop Interface
- Report, Data, and Model views – understanding each workspace
- Navigation panes, ribbon, and canvas organization
Getting Data
-
Importing data from various sources:
- Microsoft Excel workbooks and ranges
- CSV and text files with custom delimiters
- SQL Server and other relational databases
- Web sources and APIs
- SharePoint lists and document libraries
- Importing multiple files from a folder – automating data consolidation
- Parameters and dynamic data sources – building flexible, reusable queries
Power Query - Basic Transformations
- Filtering rows and sorting data to focus on relevant information
- Removing unnecessary columns and adding new calculated columns
- Changing data types and handling regional format differences
- Splitting columns by delimiter and merging columns into combined fields
- Handling errors and null values – strategies for clean data
Power Query - Advanced Transformations
- Unpivot and Pivot operations – reshaping data for analysis
- Grouping and aggregations – summarizing data at different levels
-
Query operations for combining data:
- Merge queries – joining tables based on matching columns
- Append queries – stacking tables with similar structure
- Understanding join types: inner, left, right, full outer, anti
- Fuzzy matching – joining data with approximate matches
- Conditional columns – applying business logic to create new fields
- Custom columns using M language expressions
- Working with numeric, date/time, and text data transformations
Data Modeling and DAX
Data Modeling
- Star Schema – theory and practical implementation for optimal performance
- Fact tables vs. dimension tables – understanding their roles in the model
-
Creating and managing relationships between tables:
- One-to-many and many-to-many relationship types
- Cross-filter direction – single vs. bidirectional filtering
- Cardinality settings and their impact on calculations
- Active and inactive relationships – handling multiple relationships between tables
DAX - Fundamentals
- Calculated columns vs. measures – when to use each approach
-
Aggregation functions for summarizing data:
- SUM, AVERAGE, COUNT – basic aggregations
- MIN, MAX, DISTINCTCOUNT – finding extremes and unique values
-
Logical functions for conditional calculations:
- IF and SWITCH – branching logic in formulas
- AND, OR – combining multiple conditions
- Text functions – manipulating and formatting text values
- Date functions – extracting and calculating with date components
DAX - Context and CALCULATE
- Row Context vs. Filter Context – the foundation of DAX evaluation
- CALCULATE – the most powerful function for modifying filter context
-
Filter functions for advanced analysis:
- FILTER – creating custom row-level filters
- ALL, ALLEXCEPT – removing filters for calculations like percentages
- REMOVEFILTERS – selectively clearing filters
- Iterator functions (SUMX, AVERAGEX, COUNTX) – row-by-row calculations
DAX - Time Intelligence
- Date table – creating a proper calendar table and marking it for time intelligence
-
Time analysis functions for comparing periods:
- YTD, QTD, MTD – year, quarter, and month-to-date calculations
- SAMEPERIODLASTYEAR – comparing to the same period in the previous year
- DATEADD – shifting dates by a specified interval
- PARALLELPERIOD – referencing parallel time periods
- Period comparisons – calculating growth rates and dynamic time-based KPIs
Visualization, Analytics, and Deployment
Visualizations and Report Design
- Choosing the right chart type – matching visuals to data and message
-
Core visuals configuration and best practices:
- Bar and column charts for comparisons
- Line charts for trends over time
- Pie and donut charts for part-to-whole relationships
- Scatter plots for correlation analysis
- Tables, matrices, and cards – displaying detailed and summary data
- Geographic visualizations – maps and filled maps for location-based insights
- Conditional formatting – using colors, icons, and data bars to highlight patterns
- Interactions between visuals – configuring cross-filtering and cross-highlighting
- Tooltips and Drillthrough – providing additional context and detailed views
- Bookmarks and buttons – creating interactive navigation and storytelling
- Report accessibility – ensuring reports are usable by all audiences
Analytics Features
- Analytics pane – adding trend lines, forecast lines, and reference lines
- Decomposition tree – breaking down metrics to identify root causes
- Key influencers visual – using AI to discover factors affecting outcomes
- Smart narratives – generating automated text summaries of data
- Anomaly detection – automatically identifying unusual patterns in time series
Custom Visuals
- Exploring the AppSource marketplace – finding specialized visualizations
- Importing and configuring custom visuals for specific use cases
Power BI Service
- Publishing reports from Desktop to the cloud
- Workspaces – organizing content for teams and projects
- Dashboards vs. Reports – understanding when to use each
-
Data refresh configuration:
- Scheduled refresh – automating data updates
- Gateway setup – connecting to on-premises data sources
- Sharing and permissions – controlling access to reports and data
- Row-Level Security (RLS) – restricting data access based on user roles
Hands-on Project
-
Building a complete analytics solution from provided business data
- Connecting to multiple data sources and transforming raw data
- Creating an optimized data model with proper relationships
- Developing an interactive dashboard with key performance indicators
- Implementing analytics features for deeper insights
- Publishing to Power BI Service and configuring security
Benefits for Participants
Upon completion, participants will be able to:
-
Connect to various data sources and transform raw data into analysis-ready formats
- Build efficient data models using star schema principles
- Write DAX measures for complex calculations and time intelligence
- Design interactive, visually appealing reports and dashboards
- Leverage AI-powered analytics features for deeper insights
- Publish, share, and secure reports in the Power BI Service
Benefits for Organizations
-
Improved data-driven decision making across teams
- Reduced dependency on IT for routine reporting needs
- Standardized, professional data visualization practices
- Better utilization of existing data assets
- Enhanced collaboration through shared analytics platforms
Requirements
- Working knowledge of Microsoft Excel (tables, charts, basic formulas)
- Understanding of basic data concepts (tables, rows, columns)
-
No prior Power BI experience required
This training is designed for: - Business professionals who need to analyze and present data effectively
- Excel users looking to transition to more powerful analytics tools
- Report creators who want to build interactive dashboards
- Analysts responsible for data-driven decision making in their organization
21 Hours
Testimonials (5)
the facilitators explanation
Zandile Ndaba - NTCSA
Course - Power BI for Business Analysts
The subject was taught in an engaging way, making me want to learn more.
kgotla Moncho - Martin Engineering Africa
Course - PL-300T00: Microsoft Power BI Data Analyst
Gain a lot of knowledge in a relatively short time
Mateusz Wojewoda - Solutions30 Telecom Sp. z o.o.
Course - Advanced Power BI
Machine Translated
The content was tough but that extra effort I had to put helped me remember and understand power BI better.
Melvin - TLI Group
Course - Power BI DAX Fundamentals
Discussing about our issues
