Data Management Glossary
AI Data Management
AI data management is the set of processes, tools, and practices used to manage the data that feeds AI models, both during training and inferencing. It includes:- Finding and curating the right data
- Moving and preparing data for AI pipelines
- Ensuring data is high-quality, compliant, and properly tagged (see data tagging)
- Optimizing where data is stored and how it’s accessed
- Tracking data lineage and governance for responsible AI
AI data management is the infrastructure and process layer that makes sure AI has the right data to work with.
The Important Role of Unstructured Data in AI Data Management
Most enterprise data today is unstructured: files, documents, images, videos, audio, PDFs, emails, sensor logs, etc. AI (especially foundation models and generative AI) thrives on unstructured data. Most AI use cases in the enterprise involve unstructured data. For example:
- LLMs → text, emails, reports
- Multimodal AI → images + text + video
- AI search & retrieval → documents, PDFs, data lakes
- AI-powered compliance → identifying sensitive files and preventing AI data leakage
So, managing unstructured data is critical to making enterprise AI effective.
Komprise for AI Data Management
Komprise helps enterprises manage and prepare unstructured data for AI. Here are some examples of Komrpsei AI data management:
Data Discovery & Curation
The Komprise Global File Index, or Metadatabase, catalogs unstructured data across storage silos.
- Find and classify relevant data for AI projects
- Tag and enriches data so AI models can understand it
Data Mobility & Preparation
Komprise can move or copy data to AI-friendly environments (e.g., cloud object stores, data lakes). With Komprise you can ensure only high-value, relevant data is fed to AI pipelines, which reduces costs and noise.
Data Tiering & Cost Optimization
Komprise customers are able to optimize data storage by keeping hot AI data on fast, high-performance storage, while moving cold data to lower cost tiers of stage. This approach saves on data storage costs and cloud egress costs, which can explode in AI pipelines.
Storage-Agnostic Metadata Catalog
The Komprise Global File Index is a searchable, vendor-neutral metadata layer AI tools and pipelines can query this catalog to discover useful data.
Governance & Compliance
Komprise helps track data lineage (where data came from, how it was transformed), which is essential for trustworthy and auditable AI. Komprise Smart Data Workflows also can identify and protect sensitive data in AI pipelines (e.g., PII, IP).
To summarize, without Komprise unstructured data is siloed, hard to find or move. With Komprise, unstructured data is cataloged and easy to curate for AI. Without Komprise Intelligent Data Management, AI pipelines can waste compute on noisy data AI models, whereas with Komprise you get only relevant, high-value data. AI data management can be an expensive and manual proposition. Komprise is focused on delivering automated, optimized data workflows with clear governance, tagging, and lineage tracking.
