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ADVOPS01-BP02 Create RACI matrices that define the roles and responsibilities for each key advertising process like infrastructure monitoring - Video Streaming Advertising Lens
Implementation guidanceResourcesKey AWS services

ADVOPS01-BP02 Create RACI matrices that define the roles and responsibilities for each key advertising process like infrastructure monitoring

When designing advertising workloads, define roles and set clear expectations for each stakeholder for seamless key advertising processes. By implementing this best practice, organizations can leverage RACI (responsible, accountable, consulted, and informed) matrices to establish a robust framework for accountability and decision-making.

Implementation guidance

By creating comprehensive RACI matrices, organizations can establish accountability, decision-making authority, and communication requirements for each step of the ad-serving workflow. This level of clarity assists in blocking confusion, gaps, or overlaps in responsibilities. This clarity also verifies that stakeholders understand their roles and how they contribute to the overall success of the advertising operations.

For data management specifically, implement the following approach:

  1. Establish data classification and handling processes:

    • Classify advertising data based on criticality and latency requirements (real-time bidding data, campaign configuration data, historical analytics data)

    • Define data retention policies for each classification (for example, bid data retained for 30 days, campaign data for one year)

    • Implement data lineage tracking using AWS Glue Data Catalog to document data origins, transformations, and dependencies across the advertising pipeline

  2. Structure teams around data criticality:

    • Real-time data operations team: Responsible for sub-100ms data like bidding, user profiles, and fraud detection

    • Campaign data management team: Handles near real-time data for configurations, targeting, and budgets

    • Analytics and reporting team: Manages batch processing for historical data and business intelligence

  3. Define data ownership with specific domains:

    • Assign data stewards for specific advertising domains such as:

      • Bid management domain (bid requests, responses, auction data)

      • User profile domain (demographic data, behavioral signals, privacy preferences)

      • Campaign domain (creative assets, targeting parameters, budget configurations)

      • Analytics domain (performance metrics, attribution data, reporting datasets)

    • Document domain-specific quality standards and governance responsibilities in the RACI matrix

  4. Implement data governance using AWS services:

    • Use AWS Organizations with service control policies (SCPs) to enforce data residency requirements for different Regions

    • Configure IAM roles with least-privilege permissions aligned to team responsibilities (for example, real-time team with write access to bidding data, read-only for analytics)

    • Deploy AWS Control Tower guardrails to help block unauthorized cross-account or cross-Region data transfers

    • Implement AWS Config rules to continuously audit compliance with data governance policies

  5. Establish data management processes:

    • Data cataloging: Use AWS AWS Glue Data Catalog to maintain a comprehensive inventory of advertising datasets with metadata, ownership, and classification

    • Quality monitoring: Implement automated data quality checks using AWS Glue DataBrew to validate incoming data against defined schemas and business rules

    • Workflow automation: Create AWS Step Functions workflows for data handoffs between teams, with validation checkpoints and approval gates for critical data transitions

Resources

Key AWS services

  • AWS Organizations

  • AWS IAM

  • AWS Control Tower

  • AWS AWS Glue Data Catalog

  • AWS Glue DataBrew

  • Amazon DataZone

  • AWS Systems Manager

  • AWS Config

  • AWS Step Functions