Excel & Power BI Mastery for Data-Driven Decisions

Excel & Power BI Mastery for Data-Driven Decisions

Transform Data into Insight — From Clean to Dashboard

This 3-day workshop empowers learners with the practical techniques professionals use to prepare, analyze, and visualize data in Excel and Power BI, producing business-ready insights and dashboards. Unlike a purely academic course, this training draws on real industry practices—including data cleaning, modeling, interactive visuals, and deployment—so participants leave with skills that translate directly to workplace tasks and decision support. By the end of the course, learners will not only handle raw data efficiently but will also create and publish a polished, decision-ready Power BI dashboard.

Learning Outcomes

By the end of this course, participants will be able to:

• Import and clean data using Excel and Power BI (Power Query) techniques.
• Apply advanced Excel functions, pivot tables, and data validation for reliable analysis.
• Build and optimize data models for reporting and insights.
• Create interactive and effective visualizations in both Excel and Power BI.
• Author DAX measures and use analytical calculations in Power BI.
• Publish, configure, and share Power BI dashboards for stakeholders.
• Understand the optimal roles of Excel vs Power BI in modern BI workflows.

Prerequisites

Learners should have:

• Basic familiarity with computers and spreadsheets.
• Access to Microsoft Excel (2019 or later / Microsoft 365) and Power BI Desktop installed.
• Curiosity about business data problems and analytical dashboards.

Detailed Training Outline

Excel Foundations for Data Analysis

• Excel interface & navigation
  • Ribbon, Quick Access, worksheets, navigation shortcuts
• Data entry standards
  • Formatting, data types, data validation
• Key formulas & functions
  • SUM, AVERAGE, COUNT, IF, AND/OR, LOOKUP functions

Advanced Excel Techniques

• Data cleanup & preparation
  • Text functions, Flash Fill, Remove Duplicates
  • Logical and error-handling functions
• Pivot Tables & Pivot Charts
  • Grouping, slicers, filters, calculated fields
• Excel dashboards
  • Designing effective visuals, layout best practices
• Introduction to Power Pivot
  • Using data models in Excel to support large datasets and relationships

Data Import & Transformation

• Introduction to Power Query
  • Connect to Excel, CSV, and other sources
  • Data profiling & transformation steps
• ETL basics
  • Cleaning, filtering, unpivoting, merging tables

Data Modeling in Power BI

• Power BI data model fundamentals
  • Tables, relationships, cardinality
• Creating robust models
  • Star schema concepts
  • Handling large datasets efficiently
• Calculated columns vs Measures
  • Logic and performance

DAX (Data Analysis Expressions)

• DAX fundamentals
  • Syntax and common functions
  • Aggregations (SUM, AVERAGE, COUNT)
• Analytical DAX
  • CALCULATE, FILTER, time-intelligence functions (YTD, QTD)
• Performance considerations

Analytical Visualizations

• Chart types & best practices
  • Bar, line, area, KPI cards, gauges
• Interactive elements
  • Slicers, filters, drill-throughs, bookmarks
• Custom visuals
  • Marketplace visuals and advanced charting tools

Dashboard Construction

• Report layout design
  • Storyboarding for business goals
• Interactivity & usability
  • Cross-filtering, responsive layouts
• Mobile optimization
  • Design considerations for different screens

Publishing & Sharing

• Power BI Service basics
  • Workspaces, datasets, reports
• Data refresh & scheduling
  • Refresh policies, data governance
• Collaborative workflows
  • Sharing via Teams, embedding in portals

Decision-Ready Insight Delivery

• Selecting KPIs
  • Aligning visual outputs to stakeholder decisions
• Reporting automation
  • Linked Excel reports and Power BI workflows
• Final project: Integrated dashboard
  • Real business dataset
  • Clean, model, visualize, and publish

Instructor Note

This course is delivered by an instructor with over 30 years of industry experience, focusing on real business scenarios and practical workflows rather than academic theory, preparing you for the kinds of analytics production work expected in professional roles.