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Data & Business Intelligence
Data Analyst Career Roadmap
Turn business questions into trustworthy analysis, dashboards, and decision-ready recommendations.
Beginner to IntermediateFlexible roadmapCareer roadmap
CAREER ROADMAP VIDEOHow to Become a Data Analyst | Complete Career Roadmap for Beginners
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What this career actually involves
A Data Analyst clarifies business questions, finds and validates data, analyzes patterns, and communicates findings in a form decision-makers can use.
Who this path can fit
- Career changers entering analytics.
- Business or operations professionals who work with reports and metrics.
- Learners building practical SQL, spreadsheet, dashboard, and Python skills.
Data AnalystEntry to Mid-LevelBusiness Intelligence AnalystEntry to Mid-LevelReporting AnalystEntry to Mid-LevelOperations AnalystEntry to Mid-LevelProduct / Marketing AnalystRole-dependent
SKILLS EMPLOYERS ARE ASKING FOR
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CORE CAPABILITIES
Skills to build for this career
✓
Business Question Framing
Translate vague requests into measurable questions and decisions.
✓
Excel / Spreadsheets
Clean, summarize, validate, and explore tabular data.
✓
SQL
Query, join, aggregate, and validate data.
✓
Data Quality
Identify missing, duplicated, inconsistent, or misleading data.
✓
Visualization
Build clear charts and dashboards tied to business questions.
✓
Python
Use Python and pandas when repeatable analysis or larger datasets justify it.
✓
Communication
Explain findings, limitations, and recommended next actions.
TEST YOUR SKILLS
Relevant knowledge checks
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TOOLS & PLATFORMS
Tools that support the work
Excel / Google Sheets
Fast exploration, cleaning, formulas, pivots, and reporting.
SQL
Data retrieval, joins, aggregation, and validation.
Power BI / Tableau
Interactive dashboards and business reporting.
Python / pandas
Repeatable data preparation and analysis.
Git / GitHub
Versioning analysis code and portfolio work.
REAL WORKFLOW
How the work typically flows
01
Frame the Decision
Define stakeholder, decision, metric, data source, and limitations.
02
Find and Validate Data
Locate sources and test data quality before analysis.
03
Analyze
Use spreadsheets, SQL, or Python to answer the defined question.
04
Visualize
Choose charts or dashboards that make the finding understandable.
05
Communicate
Explain what happened, why it matters, confidence, and next action.
DEVELOPMENT ROADMAP
Build capability in stages
Stage 1
Business and Spreadsheet Foundations
Learn question framing, data structure, formulas, pivots, and data-quality checks.
OutcomeAnalyze structured business data with clear metric definitions.
Stage 2
SQL Analysis
Query, join, filter, aggregate, and validate relational data.
OutcomeAnswer business questions directly from database tables.
Stage 3
Visualization and Dashboards
Choose useful charts, KPIs, filters, and dashboard layouts.
OutcomeCommunicate patterns without hiding limitations.
Stage 4
Python for Analysis
Use pandas for reusable cleaning and analysis workflows.
OutcomeExtend beyond spreadsheet-only analysis when appropriate.
Stage 5
Portfolio and Interview Evidence
Package analysis, queries, dashboards, and decision notes.
OutcomeExplain both technical work and business reasoning.
WORKPLACE SCENARIO
Online Training Company
Problem
Leaders need to understand course interest, registration drop-off, channel performance, and underperforming classes.
Objective
Turn raw operational data into trustworthy recommendations.
PORTFOLIO PROJECT
Training Business Performance Analysis
Analyze a simulated online-training business to understand course interest, registration drop-off, channel performance, and class outcomes.
Business Question Brief
Define the decision, metric, stakeholder, source, and limitations.
SQL Analysis
Queries supporting enrollment, conversion, and channel analysis.
Dashboard
A Power BI or Tableau view with documented KPI definitions.
Data Quality Report
Document missing, duplicate, or inconsistent records and how they were handled.
Decision Memo
Summarize findings, uncertainty, and recommended next actions.
PORTFOLIO EVIDENCE
What you should be able to show
SQL Query Set
Shows ability to retrieve and validate business data.
Dashboard
Shows visual communication and metric design.
Data Quality Notes
Demonstrates skepticism about source data.
Decision Memo
Shows business interpretation rather than chart production alone.
INTERVIEW PREPARATION
Turn your learning into an interview story
How do you turn a vague request into an analysis question?
Explain stakeholder, decision, metric, source, grain, and limitations.
How do you validate data before building a dashboard?
Discuss completeness, duplicates, types, ranges, joins, and business-rule checks.
When would you use SQL, Excel, or Python?
Explain trade-offs based on speed, scale, repeatability, and collaboration.
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