Advanced Power BI Analytics Training Course

Participants can build maintainable, reusable and efficient Power Query transformation pipelines.

• Profile source columns for nulls, duplicates, outliers and type errors
• Apply M functions to standardise codes, dates and currency fields
• Parameterise source paths, server names and refresh-period variables
• Build reusable Power Query functions for repeated transformation logic
• Merge and append queries while preserving cardinality and row lineage
• Use query diagnostics to isolate slow steps and folding breaks

Participants can write reliable DAX measures using context control, variables and filter logic.

• Establish filter context, row context and context transition precisely
• Write measures with CALCULATE, variables and explicit filter modifiers
• Choose SUMX, AVERAGEX and iterator patterns for non-additive calculations
• Apply ALL, REMOVEFILTERS and KEEPFILTERS without distorting report totals
• Create calculation groups for reusable measure formatting and logic
• Validate measures against controlled reconciliations and known business scenarios

Participants can create advanced analytical measures for trends, scenarios, cohorts and management variance reporting.

• Build year-to-date, rolling-period and prior-period measures using time intelligence
• Design custom fiscal calendars and role-playing date relationships
• Calculate cohort retention, variance bridges and contribution analysis measures
• Use virtual tables, TREATAS and disconnected tables for scenario logic
• Implement dynamic measure selection with field parameters and SWITCH
• Inspect query plans with DAX Studio Server Timings

Participants can configure model relationships and access controls that protect data without distorting analysis.

• Configure one-to-many, many-to-many and inactive relationships deliberately
• Resolve ambiguous filter paths through model redesign and USERELATIONSHIP
• Apply object-level and row-level security roles using DAX filters
• Test security behaviour with View As and representative identities
• Distinguish workspace permissions, app audiences and dataset build permissions
• Map sensitive fields to classification labels and access requirements

Participants can identify and remediate common model, DAX and refresh performance problems.

• Measure report latency using Performance Analyzer and visual query timings
• Reduce cardinality through column removal, encoding choices and aggregation tables
• Optimise DAX by limiting iterators, materialisation and repeated context transitions
• Configure aggregation mappings for import summaries over DirectQuery detail
• Diagnose storage-engine and formula-engine bottlenecks from server timings
• Set refresh schedules, failure alerts and gateway capacity responsibilities

Participants can design accessible reports that direct attention to valid analytical conclusions.

• Apply visual hierarchy, preattentive attributes and Gestalt grouping principles
• Select visuals according to comparison, composition, distribution and relationship tasks
• Design drillthrough, tooltips and bookmarks for guided analytical paths
• Build accessible reports using contrast, alt text and keyboard order
• Control interactions, edit interactions and cross-filtering to prevent misleading views
• Create mobile layouts that preserve priority metrics and readable detail

Participants can publish, deploy and distribute Power BI content through controlled service processes.

• Publish semantic models, reports and apps through controlled workspaces
• Configure deployment pipelines across development, test and production stages
• Use parameters and rules to manage environment-specific connections
• Schedule refreshes, configure gateways and monitor refresh history
• Define endorsement, certification and discovery practices for trusted assets
• Manage subscriptions, alerts and app audiences for report distribution

Participants can establish practical governance controls for Power BI assets, access and change.

• Establish naming conventions, ownership records and data lineage documentation
• Apply Microsoft Purview sensitivity labels to reports and semantic models
• Set workspace governance controls for sharing, export and external access
• Monitor usage metrics to retire duplicate or low-value reports
• Define release notes, change control and rollback procedures
• Audit access, refresh failures and security exceptions against operating standards

Participants can prioritise and communicate a practical improvement plan for an existing Power BI estate.

• Assess a reporting estate against model, performance and governance criteria
• Prioritise improvements using impact, effort, risk and dependency scoring
• Draft a semantic model refactoring plan with acceptance criteria
• Specify DAX validation tests for critical management measures
• Create a report performance remediation backlog with accountable owners
• Present a 90-day Power BI improvement plan to stakeholders