Explore Tasks
Define a data product's consumers, contract and roadmap and decide its next increment or retirement
Data consumers receive a data product specification (consumers, contract, service levels, adoption measures) and a prioritised roadmap including deprecation.
1job does it
1job helps with it
39skills it needs
Does itHelps with it
- Reading and tracing unfamiliar code
- Reviewing human- and AI-generated code changes for correctness and risk
- Sampling and reviewing a team's work against standards
- Diagnosing misleading data visualisations
- Verifying reports and dashboards before and after release
- Verifying AI-assisted outputs against sources
- Disclosing AI contribution to professional work
- Testing competing explanations with discriminating evidence
- Independently checking analytical conclusions and claims
- Escalating unresolved risks with evidence and clear ownership
- Giving specific developmental feedback on data and AI work
- Judging the materiality of defects and deficiencies for the intended use
- Tracing data lineage upstream and downstream
- Designing experiments
- Communicating quantified uncertainty
- Designing and versioning data contracts for consumers
- Designing decision-oriented research with customers, users or employees
- Interpreting customer feedback and qualitative evidence
- Defining measurable outcomes and leading indicators
- Prioritising work by evidenced value, cost, risk and confidence
- Evaluating product outcomes and metric integrity
- Diagnosing operational handoffs and flow
- Making accountable decisions under uncertainty
- Revising prior decisions when evidence changes
- Mapping stakeholders' decisions, constraints and needs
- Building cohort and retention analyses with correct denominators
- Setting and reviewing reliability objectives and error budgets for data and AI services
- Establishing and declaring data grain
- Reading business metrics
- Governing shared data definitions
- Writing data quality rules
- Reconciling conflicting reports
- Calculating and verifying KPIs against their specification
- Specifying decision-useful reports
- Specifying BI measure semantics: additivity, aggregation and time
- Designing semantic models for governed analytics
- Identifying keys and testing referential integrity
- Designing dimensional models with explicit grain
- Assigning and operating data ownership and stewardship
Paths that teach the skills it needs
Skill Path
Data Literacy for Business Decisions
Judge whether a business claim from a table, KPI, chart or dashboard really holds up.
- Modules
- 5 open
- Practice data
- Raket Parts
Tool Path
SQL for Analysis
Answer real business questions with SQL, from your first query to finding why a number moved.
- Modules
- 5 open
- Runs in
- Your browser
Skill Path
Data Preparation: Cleaning, Repair and Reconciliation
Check whether a table is fit for the job, then clean, repair and reconcile it with the evidence to back it.
- Modules
- 5 open
- Practice data
- Raket Parts
Coming soonManaging Data and AI Products