Data in automotive
automotive data: connected-vehicle telemetry, manufacturing and supply-chain data, quality and recalls, and data ownership/privacy.
This block builds data fluency for the automotive sector, spanning vehicle telematics, connected-car streams, manufacturing and supply chain data, dealership CRM, and warranty and quality records. You will learn which datasets drive decisions across OEMs, suppliers, and mobility services, and how to judge their quality through completeness, accuracy, lineage, and timeliness. The block covers analytics benchmarks used in production, aftersales, and fleet contexts, then moves into the regulatory reality of vehicle data, from driver privacy to type-approval traceability. It closes with governance structures and practical audit routines you can run on connected-vehicle and plant data. The goal is confident, sector-specific judgment about automotive data, not generic theory.
What you'll master
- Map the key automotive data sources and datasets from telematics to warranty and select the right ones for a given decision
- Assess automotive data quality using completeness, accuracy, lineage, and timeliness metrics tied to production and connected-car use cases
- Apply sector privacy and data regulations to connected-vehicle and personal-data flows and identify compliance gaps
- Design and run practical data governance checks and audits across OEM, supplier, and dealership systems
Key terms
Modules
How core data concepts create concrete value across telemetry, production, quality, and compliance in the automotive sector.
Mapping automotive datasets, ensuring their quality and lineage, and tracking the metrics that drive decisions.
Applying automotive privacy regulations and standing up governance, consent, and audit practices for vehicle data.
Latest articles
Recent articles from the blog that apply to Automotive.