<span data-i18n data-en="Advanced" data-bn="অ্যাডভান্সড">Advanced</span>

Data Analytics — Excel, SQL & Power BI

Build practical, job-relevant capability in Data Analytics — Excel, SQL & Power BI through guided practice, projects and a capstone.

9 chapters 57 lessons 19 hours

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Career track 04

Technology & Data Learning Path

Develop job-ready data, coding and cybersecurity capability through practical projects.

Jobs this leads to Data analysis, BI, software/web development and cybersecurity pathways

8 courses · 158 hours · ~6 months See the path

Why take this course?

Starts with Analytics thinking, questions and data quality and progresses toward end-to-end analytics case study

Includes 9 focused chapters and 57 guided lessons with practice and review

Built around practical Data Analytics — Excel, SQL & Power BI workflows rather than generic theory or income promises

What you will be able to do

✓ Explain and apply the core concepts of Data Analytics — Excel, SQL & Power BI
✓ Use the current tools and workflows used in real projects
✓ Complete guided exercises and troubleshoot common problems
✓ Produce a portfolio-ready or application-ready capstone
✓ Evaluate quality, risk, ethics and professional best practices

Full curriculum

9 chapters · 57 lessons

▶ Concepts: Analytics thinking, questions and data quality 12m FREE
▶ Setup: Analytics thinking, questions and data quality 18m FREE
🔒 Guided start: Analytics thinking, questions and data quality 18m
🔒 Practice: Analytics thinking, questions and data quality 24m
🔒 Common mistakes: Analytics thinking, questions and data quality 18m
🔒 Checkpoint: Analytics thinking, questions and data quality 16m

▶ Concepts: Excel analysis and exploratory summaries 14m FREE
🔒 Setup: Excel analysis and exploratory summaries 14m
🔒 Guided start: Excel analysis and exploratory summaries 20m
🔒 Practice: Excel analysis and exploratory summaries 26m
🔒 Common mistakes: Excel analysis and exploratory summaries 14m
🔒 Checkpoint: Excel analysis and exploratory summaries 18m

🔒 Principles: SQL querying, joins, grouping and window concepts 12m
🔒 Tools: SQL querying, joins, grouping and window concepts 18m
🔒 Guided build: SQL querying, joins, grouping and window concepts 24m
🔒 Applied exercise: SQL querying, joins, grouping and window concepts 24m
🔒 Troubleshoot: SQL querying, joins, grouping and window concepts 18m
🔒 Quality review: SQL querying, joins, grouping and window concepts 22m
🔒 Checkpoint: SQL querying, joins, grouping and window concepts 16m

🔒 Principles: Data cleaning and transformation with Power Query 14m
🔒 Tools: Data cleaning and transformation with Power Query 20m
🔒 Guided build: Data cleaning and transformation with Power Query 20m
🔒 Applied exercise: Data cleaning and transformation with Power Query 26m
🔒 Troubleshoot: Data cleaning and transformation with Power Query 20m
🔒 Quality review: Data cleaning and transformation with Power Query 18m
🔒 Checkpoint: Data cleaning and transformation with Power Query 18m

🔒 Project brief: Data modelling and relationships in Power BI 14m
🔒 Plan: Data modelling and relationships in Power BI 16m
🔒 Hands-on build: Data modelling and relationships in Power BI 30m
🔒 Real scenario: Data modelling and relationships in Power BI 30m
🔒 Review: Data modelling and relationships in Power BI 18m
🔒 Checkpoint: Data modelling and relationships in Power BI 18m

🔒 Project brief: DAX measures and business metrics 10m
🔒 Plan: DAX measures and business metrics 18m
🔒 Hands-on build: DAX measures and business metrics 32m
🔒 Real scenario: DAX measures and business metrics 26m
🔒 Review: DAX measures and business metrics 20m
🔒 Checkpoint: DAX measures and business metrics 20m

🔒 Advanced concepts: Dashboard design, storytelling and accessibility 16m
🔒 Workflow: Dashboard design, storytelling and accessibility 22m
🔒 Case study: Dashboard design, storytelling and accessibility 22m
🔒 Advanced practice: Dashboard design, storytelling and accessibility 28m
🔒 Edge cases: Dashboard design, storytelling and accessibility 22m
🔒 Optimise: Dashboard design, storytelling and accessibility 20m
🔒 Checkpoint: Dashboard design, storytelling and accessibility 18m

🔒 Advanced concepts: Validation, documentation and stakeholder communication 18m
🔒 Workflow: Validation, documentation and stakeholder communication 18m
🔒 Case study: Validation, documentation and stakeholder communication 24m
🔒 Advanced practice: Validation, documentation and stakeholder communication 30m
🔒 Edge cases: Validation, documentation and stakeholder communication 18m
🔒 Optimise: Validation, documentation and stakeholder communication 22m
🔒 Checkpoint: Validation, documentation and stakeholder communication 20m

🔒 Capstone brief: end-to-end analytics case study 10m
🔒 Plan: end-to-end analytics case study 18m
🔒 Build: end-to-end analytics case study 40m
🔒 Professional review: end-to-end analytics case study 20m
🔒 Present and reflect: end-to-end analytics case study 18m

Course guidance

AlinLearning Technology & Data Course Team

Technical foundations, projects and quality review

Lessons progress from concepts and setup into projects, troubleshooting and advanced practice.

Official reference anchors

Curriculum references used for maintenance

These links are reference sources for course maintenance. They do not imply certification, endorsement or guaranteed outcomes. Platform rules and requirements can change.

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Microsoft Learn

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Python documentation

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OWASP Top 10

Common questions

Is this course pre-recorded?

The delivery format is shown inside the course. Available lessons, videos, reading material and activities can be completed at your own pace unless a live session is specifically stated.

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Course access remains available according to the access terms shown at purchase.

What if the course is not right for me?

Check the current published Refund Policy before purchase.

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The platform can show course completion and certificate-verification features where enabled.