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Getting started - Guidance for an Automotive Data Platform on AWS
Platform Foundation Deployment (Optional)PrerequisitesDeploy SageMaker Unified StudioRegister Data ProductsConfigure Cross-Domain AccessTest Cross-Domain Query

Getting started

Platform Foundation Deployment (Optional)

Deploy SageMaker Unified Studio for centralized data governance.

Prerequisites

  • Customer 360 and/or Predictive Maintenance already deployed

  • AWS IAM Identity Center configured

  • VPC with private subnets

Deploy SageMaker Unified Studio

# Navigate to platform foundation directory
cd automotive-data-platform-on-aws/platform-foundation

# Install dependencies
npm install

# Deploy
cdk deploy PlatformFoundationStack

Deployment time: 60 minutes

What gets deployed:

  • SageMaker Unified Studio domain

  • Amazon DataZone domain

  • Lake Formation resource shares

  • IAM roles for cross-domain access

Register Data Products

Register Customer 360:

  1. Open DataZone console

  2. Create project: "Customer Analytics"

  3. Publish data product:

    • Name: customer-360-analytics

    • Source: Glue Data Catalog cx_analytics

    • Tables: All 11 tables

    • Access: Request-based approval

Register Predictive Maintenance:

  1. Create project: "Vehicle Intelligence"

  2. Publish data product:

    • Name: predictive-maintenance

    • Source: Glue Data Catalog mmt_predictive_maintenance

    • Tables: All prediction tables

    • Access: Automated approval for anonymized data

Configure Cross-Domain Access

# Grant Customer Analytics project access to Predictive Maintenance data
aws datazone create-subscription-grant \
  --domain-identifier dzd-... \
  --granted-entity '{"listing":{"identifier":"lst-...","revision":"1"}}' \
  --subscription-target-identifier st-... \
  --region us-east-1

Test Cross-Domain Query

-- Query combining Customer 360 and Predictive Maintenance data
SELECT
  c.customer_id,
  c.health_score,
  c.nps,
  p.risk_level,
  p.days_to_failure,