Our client is a non-profit organization in Texas engaged in community-based development services in the areas of economic development, immigration/citizenship services, family health, education, leadership & civic engagement, youth programs, senior programs, and many more.


The variety of services were supported by different operational systems (and some are paper-based business processes) and are not integrated enough to recognize existing customers. Customer and other master data ended up in multiple databases creating a duplicate copy of the same record, often with different information (different addresses for same customer, or inaccurate non-standard data). The client could not get information on the history of services provided for a customer nor could they recommend appropriate services to the customer due to the lack of a single, unified view.

Key gaps found from discovery phase (as-is system and process analysis):

  • No formal data governance structure exists to ensure best practices are adhered to at the project level where data is being affected.
  • Lack of enterprise-wide data architect exists to maintain data structures.
  • No clear ownership of data and lack of defined roles and responsibilities.
  • No book of record exists for client, entities and services; data is enriched and stored at the functional application layer.
  • Some of the data (surveys, course evaluations, etc.) is often obtained on paper or in MS Excel spreadsheets.

The client’s objectives in partnering with XTIVIA include:

  • Develop a single view of a client across all entities and services.
  • Implement address validation and cleansing.
  • Implement data de-duplication process.
  • Improve data quality.
  • Standardize and maintain a conformed view across the enterprise of all reference data.
  • Integrated reporting environment.
  • Formulate a governance to manage data and process.
  • Implement data stewardship and governance organization (e.g., organization, roles, and responsibilities).


XTIVIA engaged the client to analyze their current system and its future state to identify gaps and provide a solution recommendation that includes data stewardship and governance, EDW strategy and architecture, technology landscape and an EDW implementation roadmap.


  • Mentored the client on data stewardship and governance.
  • Architected the governance process.
  • Recommended organizational roles (data owner, data steward, data quality analyst, etc.).
  • Recommended key data quality metrics to track.


  • Unbiased analysis of available technologies (Database Platform, ETL Tool, BI Reporting Tool, MDM Tool, Data Quality Tool).
  • Comparative analysis of technologies in terms of TCO, ease-of-use, and ease-of-integration.
  • Source of analysis included past experience, analyst reports, third-party benchmarking, and vendor websites (no budget for formal RFI and RFQ process from client).
  • Final recommendation of technology.


  • Multiple phases of the roadmap.
  • Timelines for each phase.
  • Stakeholders, processes, and systems that are benefiting from each phase
  • Deliverables of each phase




The detailed analysis, architecture, and roadmap provided the client with a better understanding of tactical, strategic EIM goals and solution tradeoffs. The deliverables from the engagement provided the basis for cost-benefit analysis, budgeting, staffing, and risk management in implementing an EDW program.

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