[FDE-02 | Ch. 11–16] Business Scenario
A global renewable-energy company is building a unified asset-performance data product across wind farms, solar sites, and battery facilities. Data arrives from SCADA systems, vendor portals, maintenance work orders, weather feeds, finance systems, and technician spreadsheets. Asset identifiers change after component replacements; timestamps use mixed local/UTC conventions; vendors resend historical telemetry after connectivity outages; maintenance teams correct failure classifications weeks later; and some free-text notes contain employee or landowner information. Operations wants near-real-time anomaly visibility, finance wants monthly loss attribution, and data science wants point-in-time correct features for predictive maintenance.
Candidate Task: Design the enterprise data solution. Address source authority and identity, ontology/semantic modeling, event time and late corrections, integration patterns, quality/lineage/observability, sensitive-data governance, point-in-time correctness, recovery/replay, scalability, operating ownership, and evidence required before the data product is trusted for analytics or AI.
参考答案与自评要点
- Design the enterprise data solution.
- Source authority and identity.
- Ontology/semantic modeling.
- Event time and late corrections.
- Integration patterns.
- Quality/lineage/observability.
- Sensitive-data governance.
- Point-in-time correctness.
- Recovery/replay.
- Scalability.
- Operating ownership.
- Evidence required before the data product is trusted for analytics or AI.
以下为练习自评,不代表 TIIDA 官方考试评分。