Data Management Glossary
Data Services
What are Data Services?
Data services describes a range of services typically provided by enterprise IT operations teams or shared services teams, such as: data processing, data integration, data security, data reduction, data protection, data storage, and unstructured data management. Data services is a broad term that can overlap with analytics services, cloud services or professional services, but is tied to financial operations (FinOps) goals. Data services are essential for data-heavy enterprise organizations that need to manage, process, and analyze large amounts of (mostly unstructured) data to gain insights and make better business decisions.
What are some examples of data services?
Data storage services: The storage of data in various forms, including files, databases, and cloud storage. The shift to Storage as a Service (STaaS) is part of a data services strategy. Read the white paper: Getting Departments to Care About Storage Savings.- Data management services: The management of data throughout its lifecycle, including data quality management, data governance, data classification is critical to lower costs and grow data value. Data management services include analysis and line of business reporting into data storage usage and costs for showback along with data migration, data tiering, data replication and deletion.
- Data processing services: This entails the processing of data through various algorithms and techniques, including data analytics, machine learning, and artificial intelligence.
- Data integration services: This is the integration of data from multiple sources (ETL/ELT) to create a single, unified view of the data (usually for analytics) as well as real-time application of data between systems (EAI, ESB, streaming).
Array Data Services vs Storage-Independent Data Services
Storage vendors use “data services” to mean the features built into an array: snapshots, replication, deduplication, compression, encryption, and quality of service. These features protect and optimize data inside that array, and they matter.
Storage-independent data services work across arrays and clouds. They analyze, move, classify, enrich, and deliver data regardless of which vendor stores it. Unstructured data needs both, because array data services stop at the array boundary while most enterprises run file and object data on several vendors plus cloud.
The practical test: if the service still works after you replace or add a storage vendor, it is storage-independent.
What are Data Storage Management Services (DSMS)?
In 2024 Gartner started writing about Data Storage Management Services (DSMS). In 2023 Gartner published the report: Modernize Your File Storage and Data Services for the Hybrid Cloud Future.
In 2024 Gartner published: Use Data Storage Management Services to Address Exponential Growth of Unstructured Data (Gartner subscription required)
In 2025 Gartner published the DSMS Market Guide:
Gartner defines the data storage management services (DSMS) market as products and services designed to provide a unified view and orchestrate the life cycle of enterprise data residing in multicloud, hybrid and SaaS environments.
From Storage Services to Data Services
In VMblog predictions post: Unstructured Data Management Predictions for 2023: Data Insights and Automation take Center Stage, Komprise cofounder and COO Krishna Subramanian noted that enterprises are moving away from managing storage to managing data services:
“Storage teams have traditionally measured infrastructure metrics for capacity and performance such as latency, I/O operations per second (IOPS) and throughput. But given the massive growth of unstructured data, data-centric metrics are becoming paramount as enterprises move away from managing storage to managing data services in hybrid cloud infrastructure. New data management metrics look at usage indicators such as top data owners, percentage of “cold” files which haven’t been accessed in over a year, most common file size and type, and financial operations metrics such as storage costs per department, storage costs per vendor per TB, percentage of backups reduced, rate of data growth, chargeback metrics and more.”
In the same post she highlighted the changing role of storage administrators:
The storage architect/engineer will evolve to incorporate data services
“We’ll see more experienced individuals in these roles move on to cloud architect and other engineering roles while IT generalists/junior cloud engineers inherit their responsibilities. This is a challenging time for IT organizations in a hybrid model as there is still significant NAS expertise needed. Either way, the IT employees managing the storage function will need new skills beyond managing the storage hardware. These individuals must understand the concept of data services-including facilitating secure, reliable governance and access to data and making data searchable and available to business stakeholders for applications such as cloud-based machine learning and data lakes. The new storage architect will frequently analyze and interpret data characteristics, developing data management plans which factor in cost savings strategies and business demands to create new value from data. This individual will interact regularly with departments to create and execute ongoing data management processes and plans.”
In a Solutions Review post: 2023 Expert Data Management Best Practices & Predictions, Komprise cofounder and CEO Kumar Goswami noted:
“IT organizations must better understand data to improve migrations and gain maximum ROI from cloud, meet compliance requirements, deliver data services to departments, and to facilitate new value generation from data.”
He went on to say:
“To keep up with ever-changing data services demands from the business, IT will implement collaborative processes with stakeholders across many different departments such as finance, marketing, legal, research, HR. Data workflow automation will support a variety of use cases from governance and compliance to cost savings to big data analytics.”
In the 2022 Strategic Roadmap for Storage, Gartner noted (subscription required):
I&O leaders must implement intelligent data services infrastructure powered by software-defined storage and hybrid cloud IT operations….Integration of data services to the hybrid cloud platform is among the top enterprise challenges to address the need for seamless data services across the edge, the core data center and public clouds.
Read the article: Unstructured Data Growth and AI Give Rise to Data Services
How Komprise Delivers Storage-Independent Data Services
Komprise Intelligent Data Management delivers data services for unstructured data across NAS, object, and cloud storage from any vendor.
- Analysis. Komprise provides enterprise search and analytics powered by Global Metadatabase that indexes file metadata across every storage system.
- Intelligent Tiering. Transparent Move Technology tiers cold files at the file level with no rehydration penalty and cuts 70%+ of storage costs.
- Migration. Elastic Data Migration delivers 27X faster NFS migrations and Komprise Hypertransfer delivers 25X faster SMB migrations.
- Orchestration and processing. Smart Data Workflows and KAPPA data services run PII detection, tagging, enrichment, and custom processing on data in place.
- AI delivery. Komprise Intelligent AI Ingest delivers curated data sets to AI with 2X faster data flows, and Komprise Universal File MCP gives AI agents permission-aware access to files.
Array Data Services vs Storage-Independent Data Services
| Evaluation Criteria | Array Data Services Only | With Komprise |
|---|---|---|
| Scope | One storage system or vendor | All NAS, object, and cloud storage |
| Typical services | Snapshots, replication, deduplication, compression, native tiering | Analytics, file-level tiering, migration, classification, enrichment, AI delivery |
| Unit of management | Volumes, aggregates, blocks | Files, objects, and their metadata |
| Visibility | Capacity and performance per array | Data age, owner, type, growth, and cost across the estate |
| Tiering | Inside the vendor ecosystem; rehydration often required | Transparent Move Technology; no rehydration penalty |
| Data processing | Not provided | Smart Data Workflows and KAPPA data services run on data in place |
| Survives a vendor change | No | Yes |
Data Services FAQs
What are data services?
Data services are the capabilities that store, protect, move, process, govern, and deliver data to the people and applications that use it. They range from storage-level features such as snapshots and replication to data management services such as analytics, tiering, migration, classification, and delivery to analytics and AI.
What is the difference between storage services and data services?
Storage services manage capacity and performance: provisioning volumes, IOPS, latency, and uptime. Data services manage the data itself: what it is, who owns it, where it should live, how it is protected, and who can use it. Storage services are measured in terabytes and throughput; data services are measured in cost per department, risk reduced, and data delivered.
What are array data services?
Array data services are features built into a storage system, such as snapshots, replication, deduplication, compression, encryption, and native tiering. They operate on data inside that vendor’s platform and typically do not extend to other vendors’ storage.
What are storage-independent data services?
Storage-independent data services run across storage from any vendor and any cloud. For unstructured data, they include cross-silo analytics, file-level tiering, migration, classification, metadata enrichment, and AI data delivery. They keep working when a storage vendor is added or replaced.
Why do enterprises need storage-independent data services for unstructured data?
Unstructured data makes up 80% to 90% of enterprise data and typically spans several NAS vendors, object storage, and cloud. Array data services stop at the array. Policies for cost, governance, and AI need to apply to all of it, which requires services that sit above the storage layer.
What are KAPPA data services?
KAPPA data services is a feature of Komprise Smart Data Workflows that runs custom processing functions on unstructured data in place, such as tagging, enrichment, and content inspection, across any storage Komprise manages. See the KAPPA data services glossary page. See the library of pre-built KAPPA data services.
How does Komprise deliver data services for unstructured data?
Komprise Intelligent Data Management indexes all file and object data into the Global Metadatabase, then applies data services across every storage system: tiering with Transparent Move Technology, migration with Elastic Data Migration, processing with Smart Data Workflows and KAPPA data services, and delivery to AI with Komprise Intelligent AI Ingest. Customers reclaim 70%+ of primary storage capacity.