Enterprise data management services in 2026 cover far more than the storage of data. They span the layers that decide whether an organization can support reliable decisions, sound governance, and dependable AI. The stack below sets out those layers as they are commonly built into modern enterprise data platforms. Each layer is anchored to the ISG Provider Lens® Advanced Analytics and AI Services – Large and Midsize 2025 U.S. Quadrant Report, which describes the state of enterprise data as it stands today.
Read from the bottom up. Each layer rests on the one beneath it, and the strength of what sits above depends on the discipline applied below.
| 06 |
Consumption
Dashboards, reports, self-service analytics, and AI models draw on the prepared data to inform daily decisions. |
*87 percent of enterprises have already enabled analytics and BI use cases across core platforms, placing the weight of decision-making on the layers beneath. |
| 05 |
Governance and Access
Policies, permissions, and compliance controls determine who uses which data, under what conditions, and with what audit trail. |
*76 percent of organizations believe centralized governance accelerates insight delivery, while only about two-thirds have the architecture to deliver on that belief. |
| 04 |
Lineage and Quality
The controls that track how data moves through the estate and confirm it remains accurate and reconciled. Data quality management and master data management sit alongside these controls. |
*Data usability for AI is identified as the top enterprise challenge, ahead of integration, scalability, and security. |
| 03 |
Cataloging and Metadata
The metadata management layer that describes what the data is, where it lives, and what it means. Business glossaries and semantic definitions sit here. |
*Fewer than one-third of large organizations report consistent data architecture standards across the business. |
| 02 |
Storage and Modernization
The warehouses, lakes, and lakehouse platforms that hold enterprise data at scale, increasingly built on cloud-native and fabric-based architectures. |
*AI spending as a share of enterprise IT budgets has risen from roughly 2 percent to almost 6 percent within two years, placing heavier demands on the storage foundation. |
| 01 |
Sources and Ingestion
Where data enters the enterprise through the data ingestion pipeline, from operational systems, SaaS applications, event streams, and legacy databases. |
*Large enterprises now run application portfolios of close to 2,000 systems on average, setting the scale of what has to be ingested and reconciled. |
Source
*ISG Provider Lens™ 2025 Advanced Analytics and AI Services – U.S. (Midsize) report. All statistics and observations shown above are drawn from that report.
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