Applying Power BI Projects for Data Analytics Course

Lesson 1 • Installing and Configuring Power BI Desktop

Guides students through installation, initial settings, and update management. Ensures a consistent, functional workspace for all subsequent exercises.

Lesson 2 • Understanding the Power BI Ecosystem

Covers Power BI Desktop, Service, and Mobile and how they interconnect. Establishes the conceptual map students need before touching any tool.

Lesson 3 • Navigating the Power BI Interface

Introduces the ribbon, panes, and canvas layout of Power BI Desktop. Students gain the spatial familiarity needed to work efficiently throughout the course.

Lesson 1 • File-Based Data Sources

Covers importing Excel workbooks, CSV, JSON, and XML files into Power BI. Students handle the most common flat-file formats encountered in real projects.

Lesson 2 • Database and Warehouse Connections

Teaches DirectQuery and Import modes for relational databases and data warehouses. Students choose the right connectivity mode based on data volume and refresh needs.

Lesson 3 • Managing and Refreshing Data Connections

Addresses gateway configuration, scheduled refresh, and credential management in Power BI Service. Students maintain live, up-to-date reports after initial deployment.

Lesson 1 • Power Query Editor Orientation

Introduces the Query Editor interface, Applied Steps pane, and formula bar. Students understand how each transformation is recorded and can be audited or reversed.

Lesson 2 • Reshaping and Structuring Data

Teaches pivoting, unpivoting, splitting columns, and merging queries. Students transform wide or irregular datasets into normalized, model-ready structures.

Lesson 3 • Custom Columns and M Language Basics

Introduces conditional columns, custom column formulas, and foundational M syntax. Students extend built-in transformations with logic tailored to business requirements.

Lesson 4 • Core Data Cleaning Techniques

Covers removing duplicates, handling nulls, correcting data types, and trimming text. These operations form the baseline quality layer for every analytical project.

Lesson 1 • Dimensional Modeling Concepts

Explains fact tables, dimension tables, and schema patterns relevant to Power BI. Students apply modeling theory to structure data before creating relationships.

Lesson 2 • Calculated Columns vs. Measures

Distinguishes row-context calculated columns from filter-context measures and their storage impact. Students choose the right construct for each analytical requirement.

Lesson 3 • Creating and Managing Relationships

Covers the Model view, relationship dialog, and cardinality options in Power BI Desktop. Students connect tables correctly to enable accurate cross-table filtering.

Lesson 4 • Model Properties and Table Configuration

Addresses hiding fields, setting sort columns, marking date tables, and configuring synonyms. Students produce a clean, user-friendly model for report authors.

Lesson 1 • Time Intelligence Functions

Applies TOTALYTD, SAMEPERIODLASTYEAR, DATEADD, and related functions to date-based analysis. Students produce period-over-period comparisons and running totals automatically.

Lesson 2 • Core Aggregation and Logical Functions

Covers SUM, AVERAGE, COUNT, IF, SWITCH, and related functions for foundational KPIs. Students build the standard metrics used in most business dashboards.

Lesson 3 • Advanced DAX Patterns and Optimization

Introduces variables, DIVIDE, ranking patterns, and DAX Studio for performance profiling. Students write readable, efficient measures that scale to large datasets.

Lesson 4 • DAX Syntax and Evaluation Context

Explains DAX syntax rules, row context, and filter context as the foundation of all calculations. Students avoid common errors by understanding how context shapes results.

Lesson 1 • Configuring and Formatting Visuals

Covers the Format pane, conditional formatting, data labels, and tooltips. Students produce polished, branded visuals that meet professional presentation standards.

Lesson 2 • Report Layout and UX Design Principles

Applies grid alignment, whitespace, visual hierarchy, and accessibility guidelines to report pages. Students create layouts that guide the viewer's eye to key insights.

Lesson 3 • Slicers, Filters, and Interactivity

Teaches slicer types, filter pane levels, and cross-visual interaction settings. Students build reports where users can explore data without needing technical knowledge.

Lesson 4 • Bookmarks, Drillthrough, and Navigation

Implements bookmarks, drillthrough pages, and button-based navigation for guided storytelling. Students add interactivity that transforms static reports into analytical applications.

Lesson 1 • Row-Level Security Implementation

Defines RLS roles in Desktop and validates them in Service to restrict data by user identity. Students protect sensitive data while maintaining a single shared report.

Lesson 2 • Publishing Reports to Power BI Service

Walks through the publish workflow, workspace selection, and post-publish verification. Students move reports from Desktop to Service without data loss or broken visuals.

Lesson 3 • Monitoring Usage and Governance

Uses usage metrics, activity logs, and sensitivity labels to govern report adoption and compliance. Students track report health and enforce organizational data policies.

Lesson 4 • Sharing, Embedding, and Export Options

Explains share links, embed codes, export to PDF or PowerPoint, and subscription emails. Students deliver insights through the channel best suited to each stakeholder.

Lesson 1 • Solution Architecture and Planning

Designs the data flow, model structure, and report hierarchy for the full solution. Students produce an architecture plan that guides efficient, low-rework development.

Lesson 2 • Deployment, Handover, and Documentation

Covers deployment pipelines, user training materials, and technical documentation for handover. Students ensure the solution is maintainable and understandable by future owners.

Lesson 3 • Requirements Gathering and Scoping

Translates business questions into measurable KPIs, data requirements, and report specifications. Students align analytical output with stakeholder expectations before building anything.

Lesson 4 • Iterative Development and Testing

Applies agile iteration cycles, DAX validation, and visual QA to build reliable reports. Students catch errors early and incorporate feedback without disrupting the full solution.