SQL
Importance: Essential (5 of 5)
Queries, joins, and aggregates data across relational sources.
Course coverage
- SQL Fundamentals
- Advanced SQL for Analytics (planned)
← All career guides8 of 8 skills10 of 19 courses
Data and AI
Data Analyst
Turns raw data into insights, reports, and dashboards that inform business decisions.
Skill coverage
100%
Course coverage
53%
Skill coverage shows how much of the role's capability map already has a published course. Course coverage shows how much of the mapped course pipeline for this role has shipped.
- Role skills
- 8
- Published coverage
- 8
- Relevant courses
- 10
Capability map
Skills
Importance describes how central each capability is to the role. Course coverage shows where you can build the skill in the current OpenSkills catalog.
01
Analysis foundations
4 capabilities
Statistics
Importance: Very important (4 of 5)
Applies descriptive and inferential statistics to validate findings.
Course coverage
- Exploratory Data Analysis
- Probability and Statistics
- Cohort and Funnel Analysis (planned)
Spreadsheets
Importance: Very important (4 of 5)
Models, cleans, and explores data with advanced spreadsheet techniques.
Course coverage
- Spreadsheets for Data Analysis
- Excel Power Query and Pivot Tables (planned)
Data cleaning
Importance: Essential (5 of 5)
Detects and resolves quality issues before analysis.
Course coverage
- Data Wrangling
- Data Validation and Anomaly Detection (planned)
02
Insight delivery
4 capabilities
Data visualization
Importance: Essential (5 of 5)
Designs charts and dashboards that communicate findings clearly.
Course coverage
- Data VisualizationFree
- Executive Reporting and Dashboard Design, Power BI Fundamentals, Tableau Fundamentals (planned)
Business intelligence tools
Importance: Very important (4 of 5)
Builds and maintains reports in BI platforms for self-service consumption.
Course coverage
- Business Intelligence FundamentalsFree
- Looker and LookML, Google Analytics and Product Analytics Fundamentals, Power BI Fundamentals, Tableau Fundamentals (planned)
Data storytelling
Importance: Very important (4 of 5)
Frames analysis as narratives that drive decisions with stakeholders.
Course coverage
- Data Storytelling
- Cohort and Funnel Analysis, Executive Reporting and Dashboard Design (planned)
Python for analysis
Importance: Important (3 of 5)
Automates and extends analysis with notebooks and data libraries.
Course coverage
Learning path
Relevant courses
Core foundations
The concepts this role is built on.
Supporting knowledge
Adjacent knowledge that improves day-to-day judgment.
- Exploratory Data Analysis
- Probability and Statistics
- Python Fundamentals
- Advanced SQL for Analytics, Looker and LookML (planned)
Specializations
Deeper paths for particular environments or directions.
- Cohort and Funnel Analysis, Data Validation and Anomaly Detection, Excel Power Query and Pivot Tables, Executive Reporting and Dashboard Design, Google Analytics and Product Analytics Fundamentals, Power BI Fundamentals, Tableau Fundamentals (planned)
Put the map to work
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Search multiple job sources at once with queries tailored to this career, then use the skill map above to evaluate what each role actually asks for.