Data Transforming, Analysing and Visualizing using Microsoft Power BI Course

Introduction

Organizations and professionals across sectors are increasingly relying on powerful tools to turn raw data into actionable insights. Microsoft Power BI has emerged as a leading business intelligence and data visualization platform, empowering users to connect to data sources, transform data, perform advanced analytics, and create interactive dashboards that support better decision-making.

This course is designed to equip participants with the practical skills and knowledge needed to harness the full potential of Microsoft Power BI. From data import and transformation using Power Query to building complex data models with DAX (Data Analysis Expressions), the training covers the entire analytical workflow. Participants will also learn how to design compelling, real-time dashboards and reports that communicate insights clearly and effectively.

The course blends hands-on practice with real-world examples, enabling participants to confidently analyze trends, monitor performance, and share insights across teams or organizations. Whether you're working in finance, operations, development, marketing, or research, Power BI offers powerful tools to bring your data to life.

Additionally, the course introduces best practices in data storytelling, governance, and collaborative report sharing via Power BI Service and Power BI Mobile. It also includes emerging concepts such as AI-driven insights and natural language queries to enhance analytical capabilities.

By the end of the course, participants will be proficient in using Power BI to transform complex data into meaningful visual narratives and support data-informed decision-making across sectors.

Duration

5 days

Who should Attend?

This course is ideal for

·       Data analysts, business analysts, and research officers responsible for turning data into insights

·       Monitoring and Evaluation (M&E) professionals who need to visualize program data and performance indicators

·       Finance, operations, and planning officers who prepare data-driven reports and dashboards

·       IT professionals and database administrators involved in data integration and management

·       Project and program managers who require real-time insights for performance monitoring and decision-making

·       Public sector officials, NGO staff, and development practitioners working with large datasets or sectoral reports

·       Students and early-career professionals looking to build practical data analysis skills using industry-standard tools

·       Decision-makers and executives who want to leverage dashboards for strategic insights

Course Objectives

By the end of this course the learners should be able to:

·       Understand the core features and components of Microsoft Power BI, including Power BI Desktop, Power BI Service, and Power BI Mobile.

·       Connect and import data from various sources, such as Excel, databases, web services, and cloud platforms.

·       Clean, shape, and transform raw data using Power Query Editor to prepare it for analysis.

·       Build and manage data models, including relationships, calculated columns, and measures using DAX (Data Analysis Expressions).

·       Perform exploratory data analysis (EDA) to identify trends, patterns, and outliers in datasets.

·       Design and develop interactive dashboards and reports using visual elements such as charts, maps, slicers, tables, and gauges.

·       Apply best practices in data visualization and storytelling to effectively communicate insights to different audiences.

·       Publish, share, and collaborate on reports through the Power BI Service and workspace environments.

·       Utilize advanced features, such as custom visuals, Q&A (natural language queries), bookmarks, and drill-throughs.

·       Integrate AI capabilities in Power BI, including key influencers, decomposition trees, and anomaly detection for deeper insights.

Course Outline

Module One: Introduction to Self-Service BI and Modern Analytics

• Overview of Business Intelligence in the digital era
• The role of Power BI in self-service analytics
• Importance of data-driven decision-making
• Types of data analytics: descriptive, diagnostic, predictive, prescriptive
• Overview of Microsoft Power Platform (Power BI, Power Automate, Power Apps)
• Introduction to self-service BI architecture and governance
• Data ethics, privacy, and compliance considerations (e.g., GDPR)
• Cloud vs. on-premise BI solutions
• Capabilities of Power BI Desktop, Service, and Mobile

Module Two: Connecting and Transforming Raw Data with Power Query

• Navigating the Power Query Editor
• Connecting to various data sources (Excel, SQL, SharePoint, Web, APIs, etc.)
• Data transformation tools: split, merge, replace, unpivot, pivot
• Using parameters and custom functions
• Handling errors and nulls
• Creating dynamic queries with M Language
• Automating data refreshes and dataflows
• Data cleaning and profiling techniques
• Best practices in transformation and query optimization

Module Three: Building a Scalable Relational Data Model

• Principles of dimensional modeling (facts vs. dimensions)
• Creating and managing relationships (star vs. snowflake schema)
• Handling one-to-many and many-to-many relationships
• Using composite models and DirectQuery
• Optimizing data models for performance
• Creating hierarchies and calculated tables
• Implementing security with row-level security (RLS)
• Data modeling documentation and versioning
• Semantic modeling and Power BI datasets

Module Four: Advanced Calculations with DAX

• Introduction to DAX language and concepts
• Difference between measures and calculated columns
• DAX context: row context vs. filter context
• Aggregations, filters, and logical expressions
• Common DAX functions (SUMX, CALCULATE, RELATED, IF, ALL, etc.)
• Time intelligence functions (YTD, MTD, QoQ, rolling averages)
• Creating KPIs with DAX
• Troubleshooting DAX expressions and performance tips
• Using variables in DAX for readable formulas

Module Five: Designing Engaging and Interactive Dashboards

• Designing for users: understanding audiences and use cases
• Adding charts, tables, slicers, and KPIs
• Working with map visuals (filled, ArcGIS, Shape maps)
• Advanced visualizations: decomposition tree, waterfall, funnel, treemap
• Using bookmarks, drillthroughs, tooltips, and what-if parameters
• Creating mobile-optimized views
• Conditional formatting and dynamic visuals
• Embedding dashboards in Teams, SharePoint, and web portals
• Applying accessibility and inclusive design principles

Module Six: Data Storytelling and Visualization Best Practices

• Principles of effective data storytelling
• Choosing the right chart types for your message
• Using narrative techniques to guide interpretation
• Avoiding misleading visuals and cognitive overload
• Visual hierarchy, layout, and design consistency
• Integrating narrative text with visuals
• Dashboard usability testing and feedback cycles
• Real-world dashboard design examples and critiques

Module Seven: Power BI Service and Collaboration Tools

• Publishing and sharing reports and dashboards
• Creating and managing workspaces and apps
• Scheduled data refreshes and gateway configuration
• Workspace roles and permissions
• Power BI Dataflows and centralized datasets
• Using Power BI Goals and Scorecards
• Collaboration with Microsoft Teams and PowerPoint
• Exporting to PDF, PowerPoint, and embedding options
• Monitoring usage and performance with Power BI audit logs

Module Eight: Artificial Intelligence and Smart Analytics in Power BI

• AI visuals: Key Influencers, Q&A, Decomposition Tree
• Using natural language queries with Q&A visual
• Applying AI Insights from Azure Cognitive Services
• Forecasting and anomaly detection in time series data
• Smart narrative visual for auto-generated summaries
• Power BI and Copilot (AI-assisted report building)
• Machine learning models in Power BI (AutoML with Dataflows)
• Responsible AI use and interpretability in business reporting

Module Nine: Data Governance, Security, and Scalability

• Understanding Power BI tenant settings and admin roles
• Managing data access with Row-Level Security (RLS) and Object-Level Security (OLS)
• Lineage tracking and impact analysis
• Best practices for large dataset performance optimization
• Data cataloging, metadata, and data certification
• Integration with Microsoft Purview for enterprise governance
• Version control and deployment pipelines in Power BI
• Audit trails and compliance monitoring

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue

The training will be held at our Upskill Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment

Unless otherwise agreed between the two parties payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.