Lucid Technologies & Solutions Pvt. Ltd.

Large US Savings Bank and Mortgage Lender

Sector : Banking
Function : Governance

Solution Components
  • Collibra customizations
  • Lucid Workflows
  • Lucid Easy Connections
    • IBM DataStage
    • IBM Information Analyzer

Business Problem

  • Business users did not trust the data from the legacy data warehouse due to lack of transparency into lineage, transformation, and quality
  • Data stewardship and rules had recently been implemented, but the data management systems where not integrated with governance platform
  • Technical assets lacked logical models for easy business consumption
  • Tool were not available to allow stewards to maintain reference data
  • Business logic embedded in reports where not understood, cataloged, or managed
  • Business users started creating shadow data marts and reports

Lucid Approach

  • Developed a 3-phase roadmap to upgrade and expand Collibra DGC with custom workflows, dashboards, asset models, On-the-Go, and integrate it with IBM InfoSphere, IBM Cognos, ServiceNow, MuleSoft, and Tidal.
  • Upgraded Collibra DGC and deployed Collibra On-the-Go to the enterprise
  • Personalized the DGC user interface with Flagstar’s logo and color themes
  • Visibility to data lineage and transformations via integration with IBM DataStage
  • Visibility to data quality score via integration with IBM Information Analyzer and custom dashboards
  • Automation of data quality issue management through custom workflow trigger via integration with IBM Information Analyzer
  • Provided the technical team with Collibra catalog for modeling and change management via integration with IBM Information Governance Catalog
  • Enhanced the asset model to organize new integrated data
  • Developed the design for using Collibra as the source for reference data management via integration with IBM InfoSphere and custom workflow
  • Designed data sharing agreement and concept for managing in Collibra
  • Designed solution for advanced lineage using a custom SQL parser


  • Improved business trust in data warehouse information via visibility to data quality, transformation, and lineage
  • Enabled data steward ownership
  • Provided self-service catalog access to enterprise
  • Improved time-to-resolution by automating issue resolution workflow
  • Made business users less reliant on technical team through understanding of data
  • Reduced use of shadow marts