AOS

AnalystOS

Job-Ready Analytics Lab

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AnalystOS Role Path

Data Analyst

Learn tables, spreadsheets, dashboards, and simple business explanations.

A practical track for beginners who want to answer business questions with tables, dashboards, and plain explanations.

Junior Data AnalystBusiness Intelligence AnalystProduct AnalystOperations Analyst

Difficulty

Intermediate

Duration

8-10 weeks

Weekly modules

4

Start Path

Skills

Capabilities You Will Build

SQLCleaning dataReading dashboardsExcelFinding patternsComparing groupsExplaining insights

Tools

Tooling And Work Surfaces

SQLExcelPower BIPythonNotebooks

Weekly Modules

A structured timeline from fundamentals to proof.

Each week connects topics, goals, outcomes, and recommended practice so progress stays visible.

W1

Module

Answer Business Questions With Tables

Use simple filters, table connections, and groups to answer a business question.

4 topics

Topics

SQL basics
Combining tables
Grouping results
Checking answers

Goals

Use simple filters, table connections, and groups to answer a business question.

Outcomes

A working answer, a small results table, and three plain sentences about what to fix first.
A fixed answer, what changed, a quick check, and a short business summary.
W2

Module

Find Customer Risk Patterns

Compare customer groups and explain where the team should act first.

3 topics

Topics

Finding patterns
Comparing groups
Writing insights

Goals

Compare customer groups and explain where the team should act first.

Outcomes

A short risk summary, a small evidence table, and one suggested action.
W3

Module

Make Dashboards Easier To Read

Spot confusing dashboard parts and choose what should appear first.

3 topics

Topics

Dashboard reading
Choosing key numbers
Clear layout

Goals

Spot confusing dashboard parts and choose what should appear first.

Outcomes

A list of confusing parts, a better order for the numbers, and one improvement plan.
W4

Module

Clean Data And Explain Patterns

Prepare messy data, find patterns, and turn the result into simple proof.

4 topics

Topics

Excel
Python basics
Finding patterns
Recommendations

Goals

Prepare messy data, find patterns, and turn the result into simple proof.

Outcomes

A cleaned data dictionary, transformation notes, and a quality-check summary.
A notebook with clean notes, a few charts, findings, and ideas to test.

Recommended Labs

Practice work mapped to this path.

These local-content labs are designed to create evidence for the path outcome before capstone work.

SQL

Beginner

Combine Two Tables

Combine simple customer and order tables to find where money is being lost.

Output

A working answer, a small results table, and three plain sentences about what to fix first.

Start Lab

SQL

Intermediate

Find At-Risk Customers

Find which customers may leave and suggest one helpful action.

Output

A short risk summary, a small evidence table, and one suggested action.

Start Lab

Power BI

Beginner

Fix a Confusing Dashboard

Review a cluttered sales dashboard and make it easier to understand.

Output

A list of confusing parts, a better order for the numbers, and one improvement plan.

Start Lab

Excel

Beginner

Excel Cleaning Challenge

Clean a messy operational spreadsheet so it can support reliable reporting and stakeholder decisions.

Output

A cleaned data dictionary, transformation notes, and a quality-check summary.

Start Lab

Python

Intermediate

Explore Data in a Notebook

Look through messy customer activity data and find useful patterns.

Output

A notebook with clean notes, a few charts, findings, and ideas to test.

Start Lab

SQL

Intermediate

Fix a Broken Query

Fix a broken SQL query and explain what was wrong in plain language.

Output

A fixed answer, what changed, a quick check, and a short business summary.

Start Lab

Capstone

Retail Operations Dashboard

A regional retail team needs a weekly operating dashboard that explains revenue movement, stock pressure, and store-level intervention priorities.

Portfolio summary

A retail operations dashboard case study showing how raw store signals become an executive action surface.

View Capstone

Required Artefacts

01KPI definition sheet
02Cleaned operations dataset notes
03Dashboard wireframe or BI mock
04Executive readout with three recommended actions

Evaluation Criteria

01Clear operating question and metric hierarchy
02Accurate calculations and segmentation
03Readable dashboard structure
04Specific store or category recommendations
05Evidence that assumptions were checked

Outcome

Build proof recruiters can scan.

A proof page with table answers, a dashboard improvement task, and a clear business recommendation.

After completing this path, you will be able to...

Write SQL-backed evidence for business questions.
Critique dashboards and improve metric hierarchy.
Package insights into recruiter-readable case studies.