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Microsoft Power BI Master Training

Master Advanced Data Modeling, Complex DAX, and Enterprise Analytics Delivery

4.9(3,100 students)
60 Hours
Advanced
MicrosoftPower BIPower PlatformDAXPower QueryData ModelingBusiness Intelligence
Microsoft Power BI Master Training

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Course Overview

This training program provides structural mastery over Microsoft Power BI, taking business analysts and data professionals through an end-to-end cloud business intelligence lifecycle. The curriculum starts with relational data transformation via Power Query and the M language, then moves into designing performant dimensional schemas. Participants will gain deep experience writing calculated columns, measures, and time-intelligence expressions using Data Analysis Expressions (DAX). The advanced modules address scalable enterprise operations, covering Row-Level Security (RLS) policies, automated gateway refresh setups, performance monitoring via Query Diagnostics, deployment pipelines, and integrated AI capabilities.

Who Should Learn

Business Intelligence Developers, Data Analysts, and Reporting Engineers
Data Architects and Database Administrators aiming to design scalable semantic layers
Finance, Marketing, and Operations Analysts looking to build advanced predictive dashboards
IT Managers managing enterprise analytics deployments, access security, and data governance

Prerequisites

  • Strong foundational knowledge of working with structured tables, pivot summaries, or data sheets
  • Basic conceptual understanding of relational databases and common logical filtering operations

Learning Outcomes

Clean, reshape, and transform raw data strings utilizing Power Query and custom M expressions
Architect optimized Star and Snowflake dimensional schemas with clear cross-filtering behaviors
Write complex DAX calculations using advanced filter contexts, iterators, and time-intelligence functions
Design interactive executive reports featuring bookmarks, custom tooltips, and dynamic conditional styling
Configure secure, scheduled on-premise Power BI Gateways to automate cloud dataset synchronization
Implement granular user access boundaries using dynamic identity-based Row-Level Security (RLS)
Leverage Query Diagnostics and performance analyzers to optimize calculation speed and minimize file memory footprint
Orchestrate enterprise governance using deployment pipelines, workspace environments, and usage auditing metrics

Course Curriculum

1Module 1: Data Integration & Power Query Architecture
4 topics
  • Ecosystem introduction: Differentiating Power BI Desktop, Service portals, and Mobile apps
  • Establishing data connections: Importing datasets from files, relational SQL Servers, and cloud warehouses
  • Navigating the Power Query Editor interface to perform relational formatting updates
  • Transforming data: Splitting columns, managing duplicate profiles, and rewriting data types
2Module 2: Dimensional Modeling & Semantic Schema Design
4 topics
  • Engineering analytical data schemas: Defining primary/foreign keys and cross-filtering behaviors
  • Structuring performance-maximized Star Schemas vs. deeply normalized Snowflake frameworks
  • Building structural category hierarchies, user-defined groupings, and multi-tier data aggregations
  • Advanced data extraction: Merging disparate tables and appending transaction records via the M Language
3Module 3: Foundational DAX Calculations & Filter Contexts
4 topics
  • Introduction to the Data Analysis Expressions (DAX) query language syntax rules
  • Differentiating physical Calculated Columns from dynamic, context-driven Measures
  • Writing core operational aggregations using functional operators like SUM, CALCULATE, and implicit filters
  • Deploying responsive report slicers, parameters, and interactive visual-level criteria
4Module 4: Advanced DAX Engineering & Time Intelligence
3 topics
  • Evaluating internal calculation engines: Transitioning contexts and overriding data rows
  • Developing time-intelligence measures to compute YTD, MTD, and rolling year-over-year deltas
  • Authoring complex calculations using conditional branching and high-performance tabular iterators
5Module 5: Dynamic Visualization, Actions & Interactive Dashboards
3 topics
  • Constructing reports using advanced chart layouts, custom marketplace plugins, and conditional styling
  • Enhancing user experience using interactive navigation buttons, bookmarks, and page-level tooltips
  • Designing dashboards with strategic data density, clean wireframes, and responsive user paths
6Module 6: Cloud Platform Governance, Service & Gateways
3 topics
  • Publishing dashboard assets to target workspaces within the cloud-hosted Power BI Service
  • Configuring on-premise Enterprise Data Gateways to bridge local assets with cloud reports
  • Scheduling automatic data refreshes, monitoring run failures, and configuring performance alerts
7Module 7: Enterprise Security, RLS & Multi-Tool Integration
3 topics
  • Enforcing data isolation: Designing and testing dynamic security filters using Row-Level Security (RLS)
  • Managing workspace collaboration, user access groups, and application deployment permissions
  • Connecting external platforms: Interfacing with Azure Synapse Analytics, SharePoint lists, and Excel clients
8Module 8: Performance Profiling, AI Features & Capstone Release
4 topics
  • Diagnosing slow calculation steps using Performance Analyzer and Query Diagnostics logs
  • Harnessing out-of-the-box AI elements: Decomposition Trees, Key Influencer visuals, and Natural Language Q&A panels
  • Managing release lifecycles using structured Dev/Test/Prod Deployment Pipelines
  • Capstone Project: Engineering a comprehensive multi-source operational report featuring advanced model design, optimized DAX layers, and secure dynamic publishing controls

Certification

Achieve the SkillSurf Certified Power BI Enterprise Architect credential upon successfully deploying the interactive data capstone project and passing the programmatic schema assessment.

Frequently Asked Questions

A Calculated Column is evaluated row-by-row during data refresh and stored permanently within your model's database memory. A Measure does not consume storage space; instead, it calculates dynamically on the fly using CPU resources, updating automatically based on the filters or slices applied on your active report layout.
Yes. Advanced modules cover both static RLS (mapping specific values to specific security groups) and dynamic RLS (utilizing DAX functions like USERPRINCIPALNAME to automatically filter report data based on the logged-in user's corporate email profile).
The course covers both. You will begin by learning the visual data transformation buttons, then transition into writing and editing custom data functions inside the Advanced Editor using the underlying formula-based M language.