SAM #70FA3126I00000003

FEMA Seeks Data Management and Governance Services for Enterprise Analytics Modernization

FEMA is seeking contractor support to modernize and improve its enterprise data management and analytics capabilities as part of the Enterprise Data and Analytics Modernization Initiative (EDAMI): - Government Buyer: - Department of Homeland Security (DHS), Federal Emergency Management Agency (FEMA), Enterprise Architecture division - OEMs and Vendors: - Microsoft (Azure) - Databricks - Products/Services Requested: - Evaluation and improvement of data management processes and data architecture across 100+ FEMA systems - Addressing data quality and governance gaps, especially in ETL pipelines for the FEMADex analytics platform - Training for 100 data stewards - Development of a data architecture roadmap using frameworks such as TOGAF, DAMA-DMBOK, and BIZBOK - Standardization of data asset inventory, nomenclature, and KPI definitions - Support for Azure data and machine learning services, including Databricks - Unique/Notable Requirements: - Alignment with the Federal Enterprise Architecture Framework (FEAF) - Focus on improving data quality, governance, and AI integration - No specific hardware or software products or quantities are being procured; the focus is on professional services and expertise

Description

The Department of Homeland Security (DHS), Federal Emergency Management Agency (FEMA), Enterprise Architecture, requires contractor expertise to evaluate the agency’s data management processes and data architecture to address gaps in data quality and governance, by using a business and enterprise architecture approach that aligns business and IT goals using the Federal Enterprise Architecture Framework (FEAF). This effort will support FEMA’s data strategy through the Enterprise Data and Analytics Modernization Initiative (EDAMI) program office, which covers over 100 systems agency-wide, and is being built with various Azure data and ML services such as DataBricks. The EDAMI program has achieved initial operating capability in its FEMADex system but is experiencing data quality issues in its ETL pipelines as many data stewards are not properly preparing and documenting data for ingestion. As a result, data users of the FEMADex analytics platform are unable to make full use of the existing datasets loaded into the data fabric.

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