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ETS details statewide data-tool criteria, seeks vendor for MDM, governance and lakehouse
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Summary
Enterprise Technology Services presented selection criteria for a statewide master data management system, data-governance tools and a shared lakehouse; staff emphasized explainable AI matching, data lineage and federated stewardship and said FY‑26 funding is targeted for tool procurement. Meeting minutes were approved and the task force plans follow-up before the March 16 meeting.
Enterprise Technology Services (ETS) staff told the Data & AI Task Force that the office is narrowing requirements and vendors for three statewide platforms — a master data management (MDM) system, a data-governance/catalog tool and a shared lakehouse — and expects to use FY‑26 funding to begin procurement.
The ETS representative outlined core selection criteria, saying the MDM must support advanced AI/ML matching to reduce manual record review while providing explainability and traceability of matches so users can see "why it's matching" and the probability of a match. The office emphasized geospatial functionality to assess impacts to buildings and households in emergencies, multi-domain mastering (residents, structures, bridges), and real-time API connectivity to avoid loading delays.
Why it matters: the office said a unified platform aims to let departments share and secure data without removing departmental ownership. "Each business owner, each individual agency… needs to own their own data," the ETS representative said, describing a federated stewardship model that pairs departmental access controls with statewide tools.
ETS described governance-tool requirements that prioritize a dynamic, searchable data catalog that shows dataset owners, access rules and whether a dataset is accessible by role. The office also wants a business glossary to reconcile differing definitions across departments and AI-driven metadata enrichment to detect sensitive fields (for example, a Social Security number entered in an address field) and produce simple quality indicators (green/yellow/red/gray).
On the lakehouse, ETS said the platform should use open, vendor-neutral formats to limit lock-in; support secure data-sharing protocols integrated with MDM and catalog tools; provide a single portal experience for users; and include multi-engine analytics and built-in ML/AI capabilities such as support for retrieval‑augmented generation and streaming ingest.
ETS listed vendors under review — "Realtio, IBM, Tamr, Lake Fusion, and Informatica" — and said teams are using a capability-ranking 'moon chart' plus price comparisons to evaluate options. The office said some vendors are offering statewide packaged quotes that could lower per-department costs. ETS told members it is preparing detailed packaged quotes for scalability and to avoid per-record or per-source pricing surprises.
The presentation also covered governance and implementation: ETS will act as a center of excellence and provide platforms and standards, while departmental data/AI leads and data owners will continue to govern access and implement use cases. ETS said departments should submit prioritized use-case roadmaps so the office can help with statewide rollouts without duplicating effort.
Votes at a glance: the task force approved the September meeting minutes after a motion and second; the chair announced the minutes were approved following a hand/virtual-hand count.
Next steps: ETS said it hopes to select tools and share a finalized AI approach before the next task force meeting on March 16. The office also plans additional meetings with departments to refine piloting, pricing and migration plans.
Sources and attribution: quotations and descriptions above are drawn from task force remarks by the ETS representative during the public meeting. All direct quotations are attributed to the ETS representative in the transcript.
