Data
The literacy, tools, and engineering discipline behind every AI system — how to query it, model it, and run it as production infrastructure.
Analysts and engineers who want to query, clean, model, and ship data — hands-on from day one.
Beginner
Core literacy: SQL, tabular data manipulation, and your first visualizations.
Intermediate
Modeling, feature engineering, and the analytics-engineering tools real data teams run on.
Advanced
Applied ML in production, statistical foundations, and the discipline of running data as an engineering system.
Managers who need to read a query, sanity-check a dashboard, and direct a data team credibly — not build the pipeline themselves.
Beginner
Enough literacy to read a query or a notebook without a translator.
Intermediate
Understand the modern data stack conceptually — what your team's tools do and why they chose them.
Advanced
Enough applied depth to direct a technical team credibly, plus the strategic frame for data investment.
Decision-makers who need to know what data maturity buys an organization, and what governance failure costs one.
Beginner
What separates a data-driven enterprise from one that just has a lot of dashboards.
Intermediate
Data strategy and governance framing from a management (not engineering) perspective.
Advanced
Where global data and AI governance is heading — the frameworks regulators and multinational bodies are converging on.
This persona's pathway is in development — check back soon.