Power BI Course in Kenya

• Overview of Power BI components (Desktop, Service, Mobile).
• Copilot Introduction: How to use AI-powered features for data exploration
• Installing Power BI Desktop and setting up the environment.
• Navigating the Power BI interface: ribbons, panes, and views.

Hands-on Lab: Importing sample datasets and exploring Copilot.

AI-Powered Learning Experience

• AI-Driven Exploration: Query data naturally and receive instant summaries
• Visual Generation: Turn insights into rapid visuals and draft dashboards
• Workflow Acceleration: Use automated Q&A to uncover trends quickly
• Human Judgment: Build reliable data models with business context
• Strategic Control: Retain ownership of logic, accuracy, and decisions

• Connecting to various data sources (Excel, SQL, Web APIs).
• Data profiling, data types, and handling missing values.
• Advanced transformations: merging, appending, pivoting, unpivoting data.
• Using Power Query Editor for complex data shaping.

Hands-on Lab: Transforming raw data into a clean dataset.

AI-Powered Learning Experience:

• Intelligent ETL: Automates profiling, detects anomalies, and speeds preparation
• Smart Transformation: Suggests joins, infers schemas, and optimizes data flows
• Adaptive Cleaning: Builds guided pipelines for high-quality, trusted datasets
• Human Oversight: Applies business rules and compliance-specific adjustments
• Expert Control: Uses domain judgment where AI cannot reliably decide

• Designing star and snowflake schemas.
• Creating and managing table relationships.
• DAX basics: calculated columns, measures, and quick measures.
• Using DAX for basic calculations like SUM, AVERAGE, COUNT.

Hands-on Lab: Building a data model for sales data analysis.

AI-Powered Learning Experience

• Natural Language DAX: Generate formulas from plain English descriptions
• Instant Validation: Check syntax and receive intelligent relationship suggestions
• Faster Reporting: Speed up measure creation and repetitive calculation work
• Human KPI Design: Define meaningful metrics aligned with strategy
• Strategic Insight: Apply organisational context only experienced professionals provide

• Advanced DAX functions: CALCULATE, FILTER, ALL, RELATED.
• Time intelligence functions for date-based calculations (e.g., YTD, QTD).
• Performance optimization techniques: DAX query tuning, minimizing model size (Copilot flags inefficient queries, suggests optimization techniques, and generates reusable patterns).

Hands-on Lab: Creating advanced DAX measures for business insights.

AI-Powered Learning Experience

• Query Optimisation: Detects inefficiencies and recommends performance improvements
• Reusable Patterns: Generates trusted DAX structures and best-practice benchmarks
• Model Efficiency: Speeds calculations and improves overall reporting performance
• Strategic Focus: Frees time to analyse impact and guide decisions
• Informed Judgment: Balances accuracy and speed in high-stakes KPI design

• Building advanced visuals: combination charts, gauges, maps, and custom visuals
• Creating dynamic reports with slicers, bookmarks, and drill-through.
• Designing for user experience: layout, color schemes, and storytelling.
• Best practices for dashboard design and performance.

Hands-on Lab: Creating an interactive sales performance dashboard.

AI-Powered Learning Experience

• Intelligent Design: Receives AI suggestions for visuals, layouts, and colour schemes
• Guided Narratives: Generate automated summaries and accessibility-focused recommendations
• Rapid Prototyping: Accelerate dashboard drafts and optimise presentation quality
• Audience Alignment: Tailor visual stories for executives and decision-makers
• Human Impact: Craft persuasive insights that inspire action and clarity

• Publishing reports and dashboards to Power BI Service.
• Configuring dataset refresh schedules and managing gateways.
• Setting up Row-Level Security (RLS) for data access control.

Hands-on Lab: Publishing and sharing reports with user access control.

AI-Powered Learning Experience

• Intelligent Governance: Monitor refresh cycles and analyse data access behaviour
• Proactive Alerts: Receive failure notifications and smart RLS recommendations
• Operational Efficiency: Reduce troubleshooting time and manual administration effort
• Human Authority: Approve governance changes involving privacy and compliance
• Ethical Control: Ensure accountability in regulatory and policy decisions

• Using Copilot to generate natural language insights and queries.
• Automating data exploration and report generation.
• Implementing Copilot for predictive analytics and recommendations.

Hands-on Lab: Using Copilot for advanced data exploration.

AI-Powered Learning Experience

• Automated Insights: Use Copilot for first-draft reports and scenario planning
• Predictive Scale: Accelerate analysis and share forward-looking recommendations widely
• Faster Reporting: Cut manual effort and speed up decision-ready outputs
• Human Validation: Refine AI results for accuracy and business relevance
• Strategic Storytelling: Translate insights into clear, action-focused narratives for leaders

• Utilizing AI visuals like Key Influencers, Decomposition Tree, and Smart Narrative.
• Conducting clustering, anomaly detection, and forecasting.
• Interactive Q&A with natural language queries.

Hands-on Lab: Applying AI visuals to real-world business data (analysts contextualize AI forecasts for relevance and business meaning).

AI-Powered Learning Experience

• Automated Analytics: Generate forecasts, detect patterns, and surface anomalies rapidly
• Predictive Reach: Share AI-driven insights across teams to empower decisions
• Accelerated Intelligence: Deliver advanced analysis in minutes, not hours
• Human Calibration: Choose correct forecast horizons for realistic planning
• Trusted Judgment: Validate anomalies and predictions using business context and expertise

• Overview of Microsoft Fabric: Synapse, Data Factory, Data Lake, and Power BI.
• Using OneLake for centralized data storage.
• Building Synapse Dataflows for real-time data ingestion (AI automates dataflow creation, pipeline monitoring, and anomaly detection).
• Creating data pipelines for ETL processes and integrating with Power BI (manual oversight ensures enterprise architecture and regulatory governance).

Hands-on Lab: Setting up a Fabric workspace, creating dataflows, and integrating with Power BI.

AI-Powered Learning Experience

• Automated Pipelines: Generate dataflows and recommended architectures with AI
• Real-Time Monitoring: Track workloads and detect issues before disruption
• Intelligent Optimization: Improve pipeline efficiency with anomaly and metadata insights
• Strategic Oversight: Define architecture roadmaps and long-term data direction
• Governance Leadership: Uphold compliance, accountability, and ethical data decisions

Phase 1 – Task & Workflow Design

• Identify 5-7 repeatable BI tasks (data refresh, anomaly detection, dashboard publishing)
• Redesign into AI-driven workflows with clear human validation checkpoints
• Define decision boundaries between AI automation and manual oversight

Phase 2 – Strategic Implementation Choices

• Select 3 areas for Agentic AI implementation with productivity, speed, and scale justifications
• Identify 2 areas requiring manual control with risk, compliance, and ethical considerations
• Develop implementation roadmap with success metrics

Phase 3 – Productivity vs. Risk Analysis

• Quantify AI productivity improvements (time savings, error reduction, scalability)
• Assess risks of autonomous AI operations without human control
• Create governance framework balancing automation with strategic oversight

Assessment Format Options:

Individual: Comprehensive 2-3 page strategic plan Group Workshop: Collaborative whiteboard sessions with team presentations on Agentic AI integration strategies

Learning Outcome: Participants will demonstrate mastery in balancing AI automation with human expertise, ensuring Agentic AI drives productivity while maintaining strategic, ethical, and compliance controls in enterprise environments.