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Data & AI · Business intelligence and data visualization

Power BI

Create business intelligence solutions using Power Query, data modeling, DAX, visualizations, dashboards, reports, data storytelling, and performance best practices.

Move from data preparation and modeling to a complete Business Intelligence Dashboard with calculated measures, interactive visuals, filters, documentation, and a presentation-ready result.

Beginner to Advanced 6 Weeks 10 Modules Online / Classroom Business Intelligence Dashboard Project
Explore curriculum → View capstone project

Course overview

Power BI is a business intelligence platform used to connect to data, transform it, build data models, calculate business measures, and create interactive dashboards and reports.

This course introduces Power BI fundamentals, Power BI Desktop, Power Query, data cleaning, data modeling, relationships, DAX measures, visual design, filters, slicers, drillthrough, bookmarks, report performance, and sharing concepts.

The proposed capstone is a Business Intelligence Dashboard project covering data preparation, data modeling, DAX measures, interactive visuals, documentation, and a professional presentation.

A useful dashboard does more than display charts. It answers business questions, uses accurate measures, guides attention to key insights, and helps users make informed decisions.

Prerequisites

This course is designed for learners with basic computer knowledge. Basic Excel knowledge is helpful.

  • Basic computer knowledge.
  • Basic Excel knowledge is helpful.
  • Basic understanding of tables, rows, and columns.
  • Basic data-analysis awareness is helpful.
  • Basic logical thinking and problem-solving skills.
  • Power BI Desktop is recommended.

Readiness activity

Explain the difference between a dimension and a measure. Identify two business questions that a sales dashboard could answer.

Who can explore this course?

Beginners

Learn BI skills

Build practical Power BI and data-visualization skills.

Excel users

Move into BI

Turn spreadsheet-based analysis into scalable dashboards.

Business learners

Analyze performance

Understand sales, operations, finance, and customer metrics.

Career changers

Enter analytics roles

Develop practical skills for BI and data-analysis pathways.

What you will learn

  • Explain business intelligence and Power BI fundamentals.
  • Install and navigate Power BI Desktop.
  • Connect to Excel, CSV, and approved data sources.
  • Use Power Query to clean and transform data.
  • Handle missing values, duplicates, and data-type issues.
  • Build a star-schema data model.
  • Create and manage table relationships.
  • Understand fact and dimension tables.
  • Write DAX calculated columns and measures.
  • Use time intelligence and filter context concepts.
  • Create visualizations and interactive dashboards.
  • Use slicers, filters, drillthrough, and bookmarks.
  • Apply report-design and accessibility best practices.
  • Optimize Power BI reports and document business insights.

Curriculum outline

The ten-module outline moves from Power BI fundamentals to a complete Business Intelligence Dashboard. Exact Power BI version, data source, and sample dataset should be confirmed before delivery.

01

Business intelligence fundamentals

Understand how business intelligence supports data-driven decision-making.

  • Business intelligence concepts.
  • Data, information, and insight.
  • Power BI ecosystem overview.
  • Power BI Desktop, Service, and Mobile.
  • Dashboards, reports, and datasets.
  • Business questions and KPIs.

Practice: Identify a business question, its KPIs, and the data needed to answer it.

02

Power BI Desktop and data sources

Set up Power BI Desktop and connect to common data sources.

  • Power BI Desktop installation and interface.
  • Power Query Editor.
  • Data view and report view.
  • Connecting to Excel and CSV files.
  • Import versus DirectQuery concepts.
  • Refreshing data.

Practice: Connect Power BI Desktop to an Excel or CSV dataset and inspect its tables and fields.

02

Power Query data cleaning

Prepare raw data for analysis using Power Query transformations.

  • Power Query interface and applied steps.
  • Removing rows and columns.
  • Changing data types.
  • Handling missing values and errors.
  • Removing duplicates.
  • Splitting, merging, and unpivoting columns.

Practice: Clean a messy dataset by correcting data types, removing duplicates, and handling missing values.

03

Data modeling and relationships

Build a reliable data model that supports accurate reporting.

  • Fact and dimension tables.
  • Star schema concepts.
  • Creating relationships.
  • Cardinality and cross-filter direction.
  • Date tables.
  • Modeling best practices.

Practice: Create a star-schema model using sales, product, customer, and date tables.

04

DAX fundamentals

Create calculated columns and measures using DAX.

  • DAX syntax and evaluation context.
  • Calculated columns versus measures.
  • Basic DAX functions.
  • Aggregate measures.
  • Logical functions.
  • Filter context concepts.

Practice: Create measures for total sales, total quantity, and average order value.

04

Time intelligence

Analyze performance over time using DAX time-intelligence concepts.

  • Date tables and calendar functions.
  • Year-to-date and month-to-date measures.
  • Previous-period comparisons.
  • Growth and trend measures.
  • Running totals.
  • Time-based filtering.

Practice: Create year-to-date sales and year-over-year growth measures.

05

Visualizations and report design

Create clear, meaningful, and accessible Power BI visuals.

  • Choosing appropriate visuals.
  • Bar, column, line, and area charts.
  • Cards, KPIs, tables, and matrices.
  • Maps and decomposition visuals.
  • Formatting and conditional formatting.
  • Accessibility and color considerations.

Practice: Create a report page with KPI cards, trend charts, and a detailed table.

05

Interactivity and navigation

Make reports interactive and easy to explore.

  • Slicers and filters.
  • Visual interactions.
  • Drillthrough pages.
  • Bookmarks.
  • Tooltips.
  • Report navigation.

Practice: Add slicers, create a drillthrough page, and configure report navigation.

06

Advanced DAX and calculations

Build reusable and context-aware calculations for business analysis.

  • Filter functions.
  • Iterator functions.
  • Relationship functions.
  • Variables in DAX.
  • Dynamic measures.
  • Calculation groups concepts.

Practice: Create a dynamic measure that responds to slicer selections.

06

Performance and best practices

Improve report performance and maintain a professional Power BI workflow.

  • Performance Analyzer.
  • Query folding concepts.
  • Reducing data volume.
  • Optimizing visuals and DAX.
  • Documentation and naming conventions.
  • Version control and collaboration concepts.

Practice: Use Performance Analyzer to identify slow visuals and apply an improvement.

07

Sharing and governance

Understand how Power BI reports can be shared and governed responsibly.

  • Publishing reports.
  • Workspaces and apps.
  • Row-level security concepts.
  • Data sensitivity labels.
  • Refresh schedules.
  • Access and governance practices.

Practice: Create a sharing plan that identifies intended users, access levels, refresh needs, and sensitive data.

08

Capstone delivery

Complete the Business Intelligence Dashboard project and prepare a professional demonstration.

  • Define business questions and KPIs.
  • Prepare and clean the approved dataset.
  • Build a star-schema data model.
  • Create DAX measures and time-intelligence calculations.
  • Design interactive report pages.
  • Add slicers, filters, drillthrough, and navigation.
  • Test filters, visuals, and calculations.
  • Document insights, assumptions, and limitations.
  • Present the dashboard and recommendations.

Practice: Submit a complete Business Intelligence Dashboard with source data, Power BI file, documentation, and insights.

Practical exercise ideas

Complete these smaller activities before assembling the final Business Intelligence Dashboard project.

Power Query

Sales data cleanup

Clean a sales dataset by fixing types, duplicates, and missing values.

Data modeling

Star schema

Build a sales model with fact and dimension tables.

DAX

KPI measures

Create total sales, profit, margin, and average order value measures.

Time intelligence

Growth analysis

Create year-to-date and year-over-year comparison measures.

Visualization

Sales dashboard

Build a dashboard showing revenue, trends, products, and regions.

Interactivity

Drillthrough report

Create a drillthrough page for product or customer details.

Suggested six-week learning plan

This is an illustrative learning sequence. Confirm the academy's official timetable, Power BI version, data source, and sample dataset before publishing.

Weekly focus and practical milestones
Week Focus Suggested milestone
01 Power BI and business intelligence basics Connect to a dataset and inspect its structure.
02 Power Query and data cleaning Clean and transform a raw dataset.
03 Data modeling and relationships Create a star-schema model with a date table.
04 DAX and time intelligence Create KPI, growth, and trend measures.
05 Visuals, interactivity, and performance Build an interactive dashboard and optimize a visual.
06 Capstone presentation Submit and present the Business Intelligence Dashboard.
Turn business data into decisions

Capstone project

Business Intelligence Dashboard

Build a complete Business Intelligence Dashboard for a controlled, approved business scenario. Possible subjects include sales performance, retail analytics, customer behavior, operations, finance, HR analytics, or another suitable educational dataset.

Core project requirements

  • Define the business questions, users, and success criteria.
  • Identify KPIs and required measures.
  • Use an approved dataset with documented source and limitations.
  • Connect and inspect the data in Power BI Desktop.
  • Clean and transform data using Power Query.
  • Handle missing values, duplicates, and data-type issues.
  • Create a star-schema data model.
  • Create relationships between fact and dimension tables.
  • Create a date table and mark it as a date table.
  • Create DAX measures for key business metrics.
  • Create time-intelligence measures such as year-to-date and growth.
  • Build interactive report pages with appropriate visuals.
  • Add slicers, filters, drillthrough, and navigation.
  • Test filters, visuals, measures, and report interactions.
  • Document insights, assumptions, and limitations.

Quality requirements

  • Use clear and meaningful names for tables, columns, and measures.
  • Use measures rather than calculated columns where appropriate.
  • Avoid unnecessary calculated columns and duplicate data.
  • Use a date table for time-based analysis.
  • Use a star-schema model where practical.
  • Choose visuals that match the business question.
  • Use accessible colors and readable labels.
  • Avoid misleading axes, scales, or visual choices.
  • Use consistent number and date formatting.
  • Limit visuals per page to support clarity.
  • Use Performance Analyzer to review report performance.
  • Document data-source assumptions and business rules.
  • Clearly state limitations and recommended next steps.

A strong dashboard should answer a clear business question, use accurate and well-named measures, highlight meaningful insights, and help users explore the data without confusion.

Suggested project structure

Keep source data, Power BI files, documentation, and presentation materials organized for maintainability.

business-intelligence-dashboard/
├── data/
│   ├── raw/
│   ├── processed/
│   └── README.md
├── powerbi/
│   └── sales-dashboard.pbix
├── documentation/
│   ├── business-requirements.md
│   ├── data-model.md
│   ├── dax-measures.md
│   └── insights.md
├── exports/
│   └── dashboard-preview.png
├── presentation/
│   └── dashboard-presentation.pptx
├── README.md
└── .gitignore

Do not commit confidential business data, personal information, credentials, or sensitive organizational reports to a public repository.

Power BI workflow

Power BI projects are iterative. New business questions, data-quality issues, stakeholder feedback, and performance findings may require updates to the data model, DAX measures, visuals, or report design.

Business

Define questions

Identify users, KPIs, decisions, and required insights.

Data

Prepare data

Connect, clean, transform, and validate source data.

Model

Build relationships

Create a star schema, date table, and reliable relationships.

DAX

Create measures

Build reusable KPIs and time-intelligence calculations.

Visuals

Design reports

Create clear, interactive, and accessible dashboards.

Review

Test and improve

Validate results, optimize performance, and document insights.

DAX measures are calculated in the context of filters and visuals, making them suitable for dynamic KPIs such as total sales, profit margin, growth, and year-to-date performance.

Tools and technologies

The exact Power BI version, data source, and sharing platform may vary by delivery. The proposed toolkit focuses on practical Power BI business-intelligence workflows.

  • Power BI Desktop
  • Power Query
  • DAX
  • Power BI Service
  • Excel
  • CSV
  • SQL concepts
  • Data modeling
  • Data visualization
  • Git
  • GitHub
  • Visual Studio Code

Supporting concepts

  • Business intelligence, KPIs, and data storytelling.
  • Power Query transformations and applied steps.
  • Fact tables, dimension tables, and star schemas.
  • Relationships, date tables, and filter context.
  • DAX measures, time intelligence, and dynamic calculations.
  • Visual design, accessibility, and report performance.

Learning outcomes

By completing the proposed lessons and exercises, aim to demonstrate the following abilities:

  • Explain business intelligence and Power BI fundamentals.
  • Connect Power BI to approved data sources.
  • Clean and transform data using Power Query.
  • Build a star-schema data model with relationships.
  • Create DAX measures and time-intelligence calculations.
  • Design interactive and accessible dashboards.
  • Use slicers, filters, drillthrough, and bookmarks.
  • Apply report-design and performance best practices.
  • Document business insights and data limitations.
  • Build and present a Business Intelligence Dashboard.

These are learning objectives, not guarantees of employment, certification, placement, or a specific BI role. Progress depends on data-analysis practice, business understanding, DAX study, and continued learning.

Related career interests

Illustrative directions for continued learning, not job or placement guarantees.

  • BI Analyst Trainee
  • Power BI Developer Trainee
  • Data Analyst Trainee
  • Reporting Analyst Trainee
  • Business Intelligence Trainee
  • MIS Executive Trainee
  • Associate Analyst

Portfolio presentation ideas

  • Explain the business questions and target users.
  • Show the data source, cleaning steps, and data model.
  • Demonstrate KPIs, trends, and interactive filters.
  • Explain DAX measures and time-intelligence calculations.
  • Present key insights and recommended actions.
  • Discuss data limitations and future improvements.

Frequently asked questions

Who is this course for?

It is suitable for beginners, Excel users, business learners, and career changers who want to build dashboards and business intelligence reports using Power BI.

Do I need Excel experience?

Basic Excel knowledge is helpful, but it is not required. The course introduces tables, data types, and analysis concepts.

Do I need programming experience?

No. Basic computer knowledge is sufficient. Basic Excel and data-analysis awareness can help.

Will the course cover Power Query?

Yes. It covers Power Query, data cleaning, transformations, data types, missing values, duplicates, and applied steps.

Will the course cover data modeling?

Yes. It covers fact and dimension tables, star-schema concepts, relationships, cardinality, and date tables.

Will the course cover DAX?

Yes. It covers DAX syntax, calculated columns, measures, filter context, time intelligence, and advanced DAX concepts.

Will the course cover dashboards?

Yes. It covers visual selection, report design, KPI cards, charts, tables, slicers, filters, drillthrough, and bookmarks.

Will the course cover Power BI Service?

It introduces Power BI Service concepts, including publishing, workspaces, apps, sharing, refresh, and governance.

What is the capstone project?

The proposed capstone is a Business Intelligence Dashboard covering data preparation, data modeling, DAX measures, interactive visuals, documentation, and insights.

Which tools are used?

The proposed tools include Power BI Desktop, Power Query, DAX, Excel or CSV data sources, and Power BI Service concepts. Confirm the academy's selected Power BI version and data source.

How long is the course?

The supplied course information proposes a duration of six weeks. Confirm the academy's official schedule, tools, datasets, and assessment requirements.

Does this course guarantee a job?

No. The course can support practical learning and portfolio development, but it does not guarantee employment, placement, certification, or salary.

How do I enroll?

This page is a frontend course-information demonstration. Enrollment, payment, scheduling, and admission workflows are not implemented here.

Turn data into business insight

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Study Power Query, data modeling, DAX, visualizations, dashboards, and business intelligence through a practical portfolio project.

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