School of Data Engineering & Analytics · Intermediate

Power BI Data Analytics & Business Intelligence Course

Master Power BI from Power Query and data modelling to advanced DAX, security, performance and executive dashboards.

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Power BI Data Analytics & Business Intelligence course illustration at Brightnest AI Academy

Power BI Workflow and Data ConnectivityPower Query and Data PreparationData Modelling and Star SchemaDAX Measures and Calculation Context

Power BI DesktopPower BI ServicePower QueryPower BIDAX

Duration9–11 weeks72 hours

Batch startsConfirm with admissionsEnquiries open

Learning formatLive mentor-led learningConfirm with admissions

Curriculum8 modulesLabs and assessed capstone

Portfolio2 projectsPlus module evidence

LevelIntermediateCourse level

PathwayData Engineering & Analytics EngineerRelated career pathway

How you will learn

Live instructor-led sessions that connect concepts to real workplace decisions.

Guided labs and workshops in every module.

Assignments, checkpoints and practical feedback.

Portfolio documentation, demonstrations and capstone review.

Access to recordings and LMS resources according to the published batch policy.

Career preparation based on completed work and target roles.

Course curriculum

What you will learn, module by module

Build semantic models, dashboards and decision-ready business intelligence solutions. Progress from Power BI Workflow and Data Connectivity to Power BI Capstone through guided labs, assessed projects, and portfolio evidence.

01Module 1 · 5 hoursPower BI Workflow and Data ConnectivityConnect to files and databases and create a structured Power BI project.

Topics you will cover

Power BI Desktop/Service
Connectors
Import versus DirectQuery concepts
Semantic model role
Report lifecycle
Workspace basics

Tools and platforms: Power BI Desktop, Power BI Service
Portfolio evidence: Power BI project shell
Assessment: Setup checkpoint

02Module 2 · 10 hoursPower Query and Data PreparationTransform messy multi-source data into clean dimension and fact tables.

Topics you will cover

Power Query UI
M concepts
Data types
Merges/appends
Pivots/unpivots
Parameters
Query folding awareness
Data quality profiling

Tools and platforms: Power Query, Power BI
Portfolio evidence: Reusable transformation layer
Assessment: Power Query lab

03Module 3 · 8 hoursData Modelling and Star SchemaRedesign a flat dataset into a star schema and validate relationships.

Topics you will cover

Facts/dimensions
Grain
Relationships
Cardinality
Date tables
Role-playing dimensions
Surrogate keys
Model design tradeoffs

Tools and platforms: Power BI, DAX
Portfolio evidence: Production-style semantic model
Assessment: Model review

04Module 4 · 12 hoursDAX Measures and Calculation ContextBuild a reusable DAX measure layer for revenue, margin, growth, retention and targets.

Topics you will cover

Measures versus columns
Filter/row context
CALCULATE
Iterators
Variables
Time intelligence
Ranking
Percent-of-total
KPI patterns

Tools and platforms: DAX, Power BI
Portfolio evidence: DAX measure library
Assessment: DAX challenge

05Module 5 · 8 hoursVisual Analytics and Data StorytellingCreate an executive dashboard with navigation, drill-down and decision-focused storytelling.

Topics you will cover

Chart selection
Report layout
Interactions
Drill-through
Tooltips
Bookmarks
Field parameters
Accessibility
Executive storytelling

Tools and platforms: Power BI
Portfolio evidence: Executive BI dashboard
Assessment: Dashboard critique

06Module 6 · 8 hoursSecurity, Governance and Self-Service BIConfigure RLS and publish a governed report workspace for multiple audience roles.

Topics you will cover

Row-level security
Workspace roles
Semantic model access
Sensitivity
Refresh
Deployment lifecycle
Governance
Self-service standards

Tools and platforms: Power BI Service
Portfolio evidence: Secured BI workspace design
Assessment: Governance lab

07Module 7 · 7 hoursPerformance and Advanced AnalyticsDiagnose a slow report and improve model/report performance with documented changes.

Topics you will cover

Model size
Cardinality
DAX optimization
Performance Analyzer
Aggregation awareness
Incremental refresh concepts
AI/analytics features where appropriate

Tools and platforms: Power BI Desktop/Service
Portfolio evidence: Optimised report version
Assessment: Performance review

08Module 8 · 14 hoursPower BI CapstoneBuild a complete sales, finance, operations or customer BI solution with a published semantic model and dashboard.

Topics you will cover

Requirements
Data prep
Star schema
DAX
Visual storytelling
Security
Deployment
Documentation
Executive walkthrough

Tools and platforms: Power BI, Power Query, DAX
Portfolio evidence: Portfolio-ready Power BI solution
Assessment: Capstone demo and rubric

Applied portfolio

Projects you will build

2 portfolio projects plus module evidence

Portfolio project 1

Executive Sales and Margin BI

Build a governed Power BI model with DAX, drill-through, RLS and an executive dashboard.

PBIX · Data model diagram · DAX measures · Dashboard walkthrough

Portfolio project 2

Operations Performance Command Center

Create KPI dashboards for service/operations with targets, exceptions and trends.

Semantic model · Report pages · Security design · Performance review

Course value

Why this course

A Power BI portfolio should demonstrate sound data modelling, useful DAX measures, trustworthy KPIs, and dashboards that support real decisions—not visual decoration.

The curriculum progresses from Power BI Workflow and Data Connectivity to Power BI Capstone, with guided labs, assessments, and two portfolio projects: Executive Sales and Margin BI and Operations Performance Command Center.

Course fit

Who this course is for

Data analysts, MIS/BI professionals and business users building governed Power BI solutions.

IntermediateData Engineering & Analytics Engineer

PrerequisitesLearners should understand basic data analysis concepts. SQL or spreadsheet experience is helpful but not mandatory.

Practical capabilities

What you will be able to do

Connect to files and databases and create a structured Power BI project.
Transform messy multi-source data into clean dimension and fact tables.
Redesign a flat dataset into a star schema and validate relationships.
Build a reusable DAX measure layer for revenue, margin, growth, retention and targets.
Create an executive dashboard with navigation, drill-down and decision-focused storytelling.
Diagnose a slow report and improve model/report performance with documented changes.
Build a complete sales, finance, operations or customer BI solution with a published semantic model and dashboard.

Tools and platforms

Technology you will use in this course

Power BI DesktopPower BI ServicePower QueryPower BIDAX

Career relevance

Data Engineering & Analytics Engineer

This course supports the development of skills relevant to roles such as Power BI Data Analyst, BI Analyst, and Business Intelligence Developer. The strongest learner outcome is a portfolio that shows the problem, implementation, testing or evaluation, documentation and a clear explanation of decisions—not a certificate alone.

Course evidence and instruction

Course guidance

Discuss your learning pathway

Review prerequisites, learning format and project expectations with admissions before enrolment.

Get course guidance

Project evidence

Explore the course projects

Review the project briefs and deliverables to understand the work expected during the course.

Review project expectations

Technology references

Technology names identify learning tools and do not imply an employer partnership or endorsement.

Microsoft

Course FAQs

Clear answers before you enrol

Is the Power BI & Business Intelligence course suitable for beginners?

This is an intermediate-level course. Learners should understand basic data analysis concepts. SQL or spreadsheet experience is helpful but not mandatory.

What will I build during the course?

You will complete guided labs in every module and build two portfolio projects: Executive Sales and Margin BI and Operations Performance Command Center. Deliverables include working files or code, documentation, testing or evaluation evidence, and a final presentation.

Which tools and platforms are covered?

Key tools include Power BI Desktop, Power BI Service, Power Query, Power BI and DAX. Additional tools are introduced through the practical work described in each module.

How long does the course take?

The course includes approximately 72 guided learning hours across 8 modules, normally delivered over 9–11 weeks depending on batch intensity and learner practice time.

Which career paths can this course support?

The curriculum supports the development of skills relevant to roles such as Power BI Data Analyst, BI Analyst, and Business Intelligence Developer. Career outcomes depend on prior experience, project quality, interview readiness and market conditions; employment is not guaranteed.

Will I receive mentor and career support?

The course includes live instruction, lab support, assignment feedback, project reviews and career preparation covering portfolio development, CV writing, LinkedIn profile improvement, and interview guidance.

Ready to start?

Ready to start your Power BI Data Analytics & Business Intelligence journey?

Review the full curriculum, experience a live class and confirm the right starting point before enrolling.

Book a free demo class Speak with a course adviser: +91 73030 11395

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