Course Outline
1. Power BI Fundamentals: Comprehensive Review
Review core Power BI concepts to establish a standardized baseline prior to engaging with advanced analytical scenarios for government.
2. Advanced Data Modeling Patterns
Examine methodologies for designing robust Power BI data models tailored to complex operational requirements and real-world business processes.
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Implement Header–Detail structures, such as Orders and Order Line Items
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Integrate multiple business processes into a unified analytical model
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Leverage shared dimensions across Sales, Forecasting, Inventory, and other fact tables
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Manage data retained at varying levels of granularity
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Consolidate Actuals, Budgets, and Forecasts within a single framework
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Address many-to-many relationships inherent in complex business architectures
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Utilize bridge tables to resolve intricate relationship challenges
3. Composite Models
Develop strategies for integrating centralized enterprise data with localized or specialized datasets without necessitating a complete architectural reconstruction.
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Evaluate the applicability of Import, DirectQuery, and Dual storage modes
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Analyze the underlying architecture of Composite Models
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Establish direct connections to existing Power BI semantic models
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Synthesize data managed at both central and local levels
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Augment enterprise semantic models with supplementary operational data
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Incorporate local data tables and custom business logic
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Assess performance implications and design constraints associated with Composite Models
4. Mastery of CALCULATE & DAX Evaluation Context
Deepen proficiency in DAX to ensure the creation of precise and reliable calculations for complex analytical needs.
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Conduct an in-depth analysis of
CALCULATE, a critical DAX function -
Examine the impact of report interactions and selections on calculation outcomes
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Implement controls to modify filter states within business measures
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Distinguish between Row Context and Filter Context mechanisms
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Elucidate the mechanics and significance of Context Transition
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Integrate Context Transition with iterator functions for advanced computation
5. Advanced Time Intelligence & DAX Patterns
Transcend foundational calculations to address analytical challenges related to temporal data, open transactions, and shifting operational conditions.
Temporal Analysis
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Construct and utilize a Calendar dimension table
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Analyze the influence of dates and reporting periods on metric calculations
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Compute Year-to-Date, Month-to-Date, and prior-period variances
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Develop rolling-window calculations
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Benchmark current performance against historical and comparable periods
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Foundational concepts of Calendar-Based Time Intelligence
In-Progress Operations
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Assess business processes defined by Start and End Dates
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Generate reports on open orders, active projects, contracts, and analogous operational states
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Determine the status of items active at a specific point in time
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Review items active throughout a designated reporting interval
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Quantify the volume and value of ongoing business items
6. Calculation Groups
Explore techniques to streamline complex Power BI models and establish modular, reusable calculation logic.
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Explain the function of Calculation Groups and Calculation Items
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Minimize the proliferation of redundant measures within a semantic model
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Apply consistent calculation logic dynamically across diverse business metrics
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Leverage
SELECTEDMEASURE()to facilitate code reusability -
Develop standardized Time Intelligence calculations
7. Visual Calculations
Introduce an accessible methodology for executing calculations directly within Power BI visual components.
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Define Visual Calculations and identify their applicable contexts
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Contrast Visual Calculations with conventional DAX measures
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Derive calculations based on the structural layout of a visual
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Execute computations across rows, columns, and categorical dimensions
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Apply Visual Calculations to specific reporting requirements
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Determine the appropriate use of Visual Calculations versus model-level measures
8. Power BI Optimization
Investigate internal Power BI processing mechanisms and identify strategies for enhancing model and report efficiency.
Power BI Engine Mechanics
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Analyze data storage and processing via the VertiPaq engine
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Assess the impact of data volume, cardinality, and data types on system performance
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Examine how architectural design influences report speed and model footprint
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Differentiate between Formula Engine and Storage Engine operations
Performance Analysis with DAX Studio
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Identify computationally intensive or slow-executing calculations
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Review model size and data distribution patterns
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Isolate specific performance bottlenecks
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Utilize performance metrics to refine models and measures
Model Management with Tabular Editor
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Review and manage semantic model metadata
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Streamline the process of implementing model modifications
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Administer Calculation Groups effectively
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Employ Best Practice Analyzer to detect areas for improvement
9. Enterprise Semantic Model Management
Examine protocols for the secure maintenance, management, and deployment of Power BI solutions across enterprise infrastructure.
Optimized Data Refresh
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Define the mechanics of Incremental Refresh
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Restrict refresh operations to modified data only
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Configure historical retention and refresh window parameters
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Analyze the function of partitions in managing extensive datasets
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Implement Incremental Refresh for large-scale enterprise models
Dynamic Row-Level Security
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Implement user-specific data access controls based on identity verification
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Transition from static to dynamic security frameworks
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Develop security mapping structures
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Leverage user authentication to dictate data visibility
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Validate and test security rule implementation
Deployment Pipelines
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Orchestrate Power BI content across Development, Testing, and Production environments
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Explain the functions of distinct pipeline stages
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Analyze variances between environmental states
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Execute controlled deployment of reports and semantic models
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Configure settings specific to each deployment environment
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Support a disciplined enterprise release lifecycle
Requirements
Participants are required to have completed the foundational Power BI course.
Testimonials (2)
The most valuable takeaway was learning how to apply the concepts in real-world scenarios and understanding the tools and processes.
Marcel Tansae - DB Technology
Course - Microsoft Power Automate
How to use relationships in Power BIand the differences between columns and measurements
