Project Deliverables

Discovery Sessions with Business and Application Team for 2 weeks to understand the use cases and data requirement for building data foundation

• Business Requirement Document for all use cases in scope.

• Data capture document for all the five (5) use cases in scope which includes details around data flow from source to target including tables, fields, data structures, mapping and transformation.

• Define and document On Data Strategy (Data Supply Chain)

  • Data Platform Architecture with supported tools and technology for each data platform component.

  • Data Quality & Governance

  • Data Management (Metadata, Data Lineage)

  • Data Operations (Backup & Archival)

  • Infrastructure sizing and technical deployment

  • Platform & Data Security Architecture

  • Network Topology diagram

  • Data As-A-Service

  • Model As A Service

• Build Data Model (Entity Relationship diagram, Logical and Physical) for manufacturing data domain.

• Configure and set up Data Platform segregated by data zones with the necessary tools and technologies required to support the functional, non-functional, and technical requirement as mentioned in this document.

• Set up a Sandbox environment within the data platform for building data foundation to support advanced analytics use cases.

• Data Platform Integration with the client’s Applications and 3rd party system as required

• Build and deploy the following Manufacturing Use Cases within the client’s Data Platform

• Build Data Profiling, Data Cleansing, Data Cataloguing of data by applying data quality checks before ingesting the data.

• Ingest, curate and process data from MES systems, factory applications, enterprise applications, data repositories and databases into the data lake and enterprise Datawarehouse as required to build the data foundation (segregated by data zones). Scope of data foundation will be determined through the requirement gathering sessions.

  • Build Data Foundation for Factory 1 ex. Solar Cells and Solar Panels data.

  • Build Data Foundation for Factory 2 ex. Power Generation through Coal based Power Plant data.

  • Build Data Foundation for Research and Development (R&D) team within the Sandbox environment for building advanced analytics use cases. Integrate Sandbox environment with Opensource tools and technologies for data mining and build analytical models.

• Build End-to-End Traceability solution (Ingest, curate, process and store data for enabling E2E Traceability. Co-relate and stitch the various data sets into one meaningful data schema. Generate insights and search capability to track and trace products from procurement of raw materials to end customer. Provide search capability function to Traceability data supported by full text search and faceted text search capabilities.

• Build Data Foundation for Reliability and Test lab data solution (Capture reliability test and lab data from Quality and Reliability applications. Ingest, curate and process the data in Data Lake & EDW).

• Build Semantic Layer for Business Users to access for Self-Service reporting.

• Design Report Templates & develop Reports & Dashboards for End-to-End Traceability Use Case.

• Implement Platform & Data Security. Set up data platform monitoring and event logs.

• Build Data Lineage & Metadata Management.

• Set up Data Archiving & Retention of data across data platform. Set up data life cycle policy to move less frequently accessed data to archive store.

• Enable data services capability for the data platform for inbound and outbound data requirements both in batch mode and real time (event driven).

• All required agile project artifacts.