Analyzing and Visualizing Data with Power BI
- Import and clean data from Excel, CSV and database sources using Power Query transformations.
- Design a star-schema model with fact and dimension tables, a date table and correct relationships.
- Write DAX measures for totals, ratios, year-to-date and prior-period comparisons.
- Build report pages with slicers, drill-down, drillthrough and tooltips that answer specific business questions.
- Publish a report to a workspace, schedule refresh and apply row-level security for different user groups.
- Power BI Components and Workflow
- Power BI Desktop, service and mobile
- From raw data to shared report
- Defining business questions and KPIs
- Preparing Data with Power Query
- Connecting to common data sources
- Cleaning, splitting, merging and appending
- Data profiling and query folding basics
- Data Modelling
- Fact and dimension tables
- Relationships, cardinality and filter direction
- Date tables and hierarchies
- DAX for Analysis
- Calculated columns versus measures
- CALCULATE and filter context
- Time intelligence functions
- Visualising and Analysing
- Choosing visuals for comparison, trend and composition
- Interactivity with slicers, drillthrough and bookmarks
- Built-in analytics such as trend lines and forecasts
- Publishing and Sharing
- Workspaces, apps and sharing options
- Scheduled refresh and gateways
- Row-level security
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Program Professional Framework
Analyzing and Visualizing Data with Power BI
Program Overview
Many teams still assemble monthly reports by copying data between spreadsheets. This programme follows the complete Power BI workflow that replaces that effort: connecting to and shaping data in Power Query, building a star-schema data model, writing core DAX measures, designing interactive report pages, and publishing and sharing content securely in the Power BI service. Participants work on a realistic operational dataset and finish with a report that refreshes automatically and answers defined business questions.
Learning Outcomes
- ✓Import and clean data from Excel, CSV and database sources using Power Query transformations.
- ✓Design a star-schema model with fact and dimension tables, a date table and correct relationships.
- ✓Write DAX measures for totals, ratios, year-to-date and prior-period comparisons.
- ✓Build report pages with slicers, drill-down, drillthrough and tooltips that answer specific business questions.
- ✓Publish a report to a workspace, schedule refresh and apply row-level security for different user groups.
Target Audience
- Business and financial analysts
- Reporting officers in government and semi-government entities
- Operations and sales performance analysts
- Excel power users moving to Power BI
Detailed Program Modules
01Power BI Components and Workflow
- Power BI Desktop, service and mobile
- From raw data to shared report
- Defining business questions and KPIs
02Preparing Data with Power Query
- Connecting to common data sources
- Cleaning, splitting, merging and appending
- Data profiling and query folding basics
03Data Modelling
- Fact and dimension tables
- Relationships, cardinality and filter direction
- Date tables and hierarchies
04DAX for Analysis
- Calculated columns versus measures
- CALCULATE and filter context
- Time intelligence functions
05Visualising and Analysing
- Choosing visuals for comparison, trend and composition
- Interactivity with slicers, drillthrough and bookmarks
- Built-in analytics such as trend lines and forecasts
06Publishing and Sharing
- Workspaces, apps and sharing options
- Scheduled refresh and gateways
- Row-level security
Training Methodology
Applied Project & Assessment
Applied Project
Participants build and publish a Power BI report for a provided service operations dataset, including a cleaned data model, at least eight DAX measures, three report pages with drillthrough, scheduled refresh and role-based security for two user groups.
Assessment
Short diagnostic at the start, practical tasks linked to each learning outcome, and evaluation of the applied project against published criteria.


