Advanced Analytics with Power BI Course

Lesson 1 • Navigating the Power BI Interface

Explores Report, Data, and Model views plus the ribbon layout. Builds spatial familiarity that accelerates all hands-on tasks.

Lesson 2 • Connecting to Common Data Sources

Demonstrates connections to files, databases, and cloud services. Provides the entry point for all data ingestion workflows.

Lesson 3 • Installing and Configuring Power BI Desktop

Guides through installation, update management, and initial settings. Ensures a consistent environment before data work begins.

Lesson 4 • Power BI Ecosystem Overview

Covers Desktop, Service, Mobile, and Gateway roles within the platform. Establishes the mental model needed for all subsequent chapters.

Lesson 1 • Shaping and Restructuring Data

Teaches pivoting, unpivoting, splitting, and merging columns. Enables analysts to reshape any raw layout into a model-ready structure.

Lesson 2 • Query Organization and Performance

Covers query groups, reference queries, and load optimization settings. Ensures pipelines remain maintainable and performant at scale.

Lesson 3 • Essential Data Cleaning Techniques

Covers removing duplicates, handling nulls, and correcting data types. Directly addresses the most common data quality issues encountered in practice.

Lesson 4 • Advanced Query Techniques

Explores conditional columns, custom columns, and parameterized queries. Builds flexibility for dynamic and reusable transformation logic.

Lesson 1 • Model Optimization and Best Practices

Covers column hiding, data type optimization, and relationship validation. Produces lean, well-documented models ready for enterprise use.

Lesson 2 • Calculated Columns vs. Measures

Distinguishes row-context calculated columns from filter-context measures. Prevents the most common modeling mistakes before DAX is introduced.

Lesson 3 • Date Table Design and Time Intelligence

Teaches building a dedicated date table and marking it for time intelligence. Enables all DAX time intelligence functions introduced in the next chapter.

Lesson 4 • Creating and Managing Relationships

Covers relationship creation, cardinality options, and cross-filter direction. Directly controls how visuals aggregate and filter data across tables.

Lesson 1 • Logical and Conditional Functions

Covers IF, SWITCH, AND, OR, IFERROR, and ISBLANK for conditional logic. Enables dynamic measure behavior based on data conditions.

Lesson 2 • DAX Syntax and Evaluation Context

Explains DAX syntax rules, row context, and filter context mechanics. This conceptual grounding prevents logic errors in every measure written afterward.

Lesson 3 • Text, Date, and Math Functions

Introduces FORMAT, CONCATENATE, date extraction, and rounding functions. Completes the core function library needed for real-world reporting.

Lesson 4 • Filter Functions and CALCULATE

Teaches CALCULATE, FILTER, ALL, ALLEXCEPT, and REMOVEFILTERS. Unlocks the ability to override and manipulate filter context in measures.

Lesson 1 • Advanced Iterator and Table Functions

Explores ADDCOLUMNS, SUMMARIZE, CROSSJOIN, and GENERATE for virtual tables. Enables sophisticated multi-table analytical patterns.

Lesson 2 • Time Intelligence Functions

Covers TOTALYTD, SAMEPERIODLASTYEAR, DATEADD, and PARALLELPERIOD. Requires the marked date table built in Chapter 3.

Lesson 3 • Ranking and Topn Patterns

Teaches RANKX, TOPN, and dynamic ranking measures for leaderboard visuals. Enables competitive and performance-ranking analytics.

Lesson 4 • Variables and Measure Optimization

Introduces VAR and RETURN for readable, performant DAX expressions. Reduces redundant evaluation and simplifies complex measure logic.

Lesson 1 • Advanced Visual Techniques

Explores small multiples, custom visuals, and field parameters for flexibility. Elevates reports beyond standard out-of-the-box capabilities.

Lesson 2 • Interactivity and Navigation Design

Teaches slicers, cross-filtering, bookmarks, and page navigation buttons. Transforms static reports into guided analytical experiences.

Lesson 3 • Choosing the Right Visual Type

Maps analytical questions to appropriate chart types and visual encodings. Prevents misleading or ineffective visual choices in reports.

Lesson 4 • Formatting and Theming Reports

Covers conditional formatting, custom themes, and brand alignment. Produces polished, consistent reports that meet organizational standards.

Lesson 1 • Monitoring Usage and Adoption

Uses usage metrics, audit logs, and the Admin portal to track adoption. Provides data-driven insight into report performance and user engagement.

Lesson 2 • Workspace Administration and Roles

Covers workspace creation, role assignments, and content organization. Establishes the governance structure for team-based Power BI deployments.

Lesson 3 • Data Refresh and Gateway Configuration

Teaches scheduled refresh, incremental refresh, and on-premises gateway setup. Ensures datasets stay current without manual intervention.

Lesson 4 • Apps, Dashboards, and Distribution

Covers building Power BI apps, pinning dashboard tiles, and audience-based distribution. Enables scalable content delivery to large user groups.

Lesson 1 • Built-in Analytics and Forecasting

Applies trend lines, error bands, forecasting, and anomaly detection in visuals. Adds statistical depth to standard time-series and trend reports.

Lesson 2 • Azure Machine Learning Integration

Connects Power BI to deployed Azure ML models via Power Query. Enables scoring of dataset rows with enterprise machine learning predictions.

Lesson 3 • Cognitive Services and AutoML in Dataflows

Applies text analytics, sentiment scoring, and AutoML within Power BI dataflows. Delivers AI enrichment at the data preparation layer for reuse across reports.

Lesson 4 • R and Python Visuals Integration

Embeds R and Python scripts as visuals for custom statistical charts. Extends Power BI's native capabilities with open-source analytics libraries.