Approach:

Through Adastra's best practice methodology, we will deliver a pilot MDM solution, that can be expanded upon in future stages.

Scope:

• Limited to 2-3 source systems to 1 domain of customer, product, supplier, vendor, employee, or legal entity
• Consolidation style MDM for a quick win with limited matching rules
• Up to 50 fields total for the domain

Assumptions/Dependencies:

• Business SMEs at the client’s organization must be available and engaged
• Adastra must have access to production data and systems at the client’s organization
  • The MDM business case must be established
  • The MDM technology must be installed and configured within the client’s environment
  • The solution development will be complete for a limited functional scope
  • The scope of work will not be deployed to production in this phase as dependencies arise to client QA, user acceptance (UAT) and production deployment cycles
  • Out of scope functional items:
    • Business and technical workflows
    • Upstream/downstream system integration
    • ESB integration
    • MDM authoring capabilities, and fully defined user role security

Client Requirements:

• Business SME availability

Next Steps:

• Extension of MDM pilot implementation
• Duration: 14 Weeks

Activities:

• Define and implement the data model for the data domain in scope
• Design and ingest data, implement data quality rules and processes for filtering, parsing, standardization, cleansing, validation, and enrichment for identified domain data elements
• Define and implement matching and consolidation fields, rules and processes for the supplier domain
  • Define the ‘Golden Record’ and its lineage to the source
• Define and implement master data governance business workflows and processes
• Assess usage of AWS Glue Data Catalog to index the location, schema, and runtime metrics of your data.

Deliverables:

• A data model for the domain in scope
• Data quality rules implementation, process and procedure
• Mastering/consolidation rules, process and procedure
• Data quality and master data governance business processes and RACI (responsible, accountable, consulted, informed)
• CRUD (create, read, update, delete) lifecycle
• An MDM solution for phase 1
• A processes to ingest data and implement data quality rules - filtering, parsing, standardization, cleansing, validation, and enrichment
• A processes to implement matching and consolidation rules and its lineage to source
• Master data governance business workflows and processes

Outcomes:

• MDM Pilot Implementation
• A ready-to-use MDM