Data Management Glossary nnn
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A
- Active Storage
- Adaptive Data Management
- AI Agents
- AI and Corporate Data
- AI Compute
- AI Data Extraction
- AI Data Governance
- AI Data Ingestion
- AI Data Leakage
- AI Data Management
- AI Data Pipelines
- AI Data Preparation
- AI Data Workflows
- AI Inferencing
- AI Infrastructure
- Air Gap
- Alternate Data Streams (ADS)
- Amazon (AWS) S3 Intelligent Tiering
- Amazon FSx
- Amazon Glacier (AWS Glacier)
- Amazon S3 (AWS S3)
- Amazon S3 Glacier Instant Retrieval
- Amazon Tiering
- Analytics-driven Data Management
- Application Programming Interface (API)
- Archival Storage
- Archiving
- Artificial Intelligence (AI)
- AWS DataSync
- AWS Lambda
- AWS Snowball
- AWS Storage
- Azure Data Box
- Azure NetApp Files
- Azure Storage
- Azure Tiering
-
C
- Capacity Planning
- Carbon footprint
- Carbon Usage Effectiveness
- Chain of Custody
- Chargeback
- Checksum
- Cloud Archiving
- Cloud Cost Optimization
- Cloud Costs
- Cloud Data Analytics
- Cloud Data Growth Analytics
- Cloud Data Management
- Cloud Data Migration
- Cloud Data Storage
- Cloud File Storage
- Cloud Migration
- Cloud NAS
- Cloud Object Storage
- Cloud Storage Gateway
- Cloud Tiering
- CloudPools
- Cold Data
- Common Internet File System (CIFS)
- Compression
-
D
- Dark Data
- Data Analytics
- Data Archiving
- Data Backup
- Data Center Consolidation
- Data Center Emissions
- Data Classification
- Data Curation
- Data Governance
- Data Hoarding
- Data Indexing
- Data Lake
- Data Lakehouse
- Data Lifecycle Management
- Data Lineage
- Data Literacy
- Data Management
- Data Management for AI
- Data Management Policy
- Data Migration
- Data Migration Chain of Custody
- Data Migration Plan
- Data Migration Software
- Data Migration Warm Cutover
- Data Mobilization
- Data Orchestration
- Data Protection
- Data Retention
- Data Retrieval
- Data Services
- Data Silos
- Data Sprawl
- Data Storage
- Data Storage Costs
- Data Storage Management Services (DSMS)
- Data Storage Optimization
- Data Storage Tags
- Data Tagging
- Data Tiering
- Data Transfer
- Data Virtualization
- Deduplication
- Deep Analytics
- Dell PowerScale
- Dell PowerScale SmartPools
- Department Showback
- Digital Business
- Digital Pathology Data Management
- Direct Data Access
- Director (Komprise Director)
- Disaster Recovery
- Dynamic Data Analytics
- Dynamic Links
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E
-
F
-
G
-
H
-
I
-
K
-
M
-
N
-
O
-
P
-
R
-
S
- S3
- S3 Data Migration
- S3 Intelligent Tiering
- Scale-Out Grid
- Scale-Out Storage
- Secondary Storage
- Sensitive Data Detection
- Shadow AI
- Shadow IT
- Sharding
- Shared-Nothing Architecture
- Showback
- Smart Data Workflows
- SmartPools
- SMB Data Migration
- SMB protocol (Server Message Block)
- Solid State Drives (SSDs)
- Storage Area Network (SAN)
- Storage Array
- Storage as a Service
- Storage as a Service (STaaS)
- Storage Assessment
- Storage Costs
- Storage Efficiency
- Storage Insights
- Storage Metrics
- Storage Pool
- Storage Reclamation
- Storage Refresh
- Storage Tiering
- Stubs
- Sustainable Data Management
- Symbolic Link
- System Metadata
-
U
- Unstructured Data
- Unstructured Data AI
- Unstructured Data Analytics
- Unstructured Data Classification
- Unstructured Data Governance
- Unstructured Data Management
- Unstructured Data Migration
- Unstructured Data Preparation
- Unstructured Data Storage
- Unstructured Data Tiering
- Unstructured Data Workflows
- Unstructured Metadata
Unstructured Data Workflows
Unstructured data workflows can include a variety of processes and technologies, such as data management tools, document management systems, content management systems, and collaboration platforms. Data is no longer static and needs to move between systems and clouds to satisfy changing requirements and to support big data and AI/ML initiatives. Technologies and processes that automate and streamline these workflows can shave significant time and costs from finding, preparing and moving data into data lakes and analytics platforms or to meet compliance requirements.
Overall, unstructured data workflows play an important role in modern data management and are critical for organizations that generate and use large volumes of unstructured data. By implementing effective unstructured data workflows, organizations can ensure that data lives at the right place and at the right time to satisfy a variety of enterprise and departmental needs.
Komprise Smart Data Workflows for File and Object Data
Komprise Smart Data Workflows allow you to define and execute automated processes, which could be industry or domain specific, to search and fine, migrate and tier, and ultimately get greater value from unstructured data. With Smart Data Workflows you can create custom queries across hybrid, multi-cloud, on-premises and edge data silos to find the file and object data you need, which is often locked away in data storage silos, execute Komprise or external functions on a subset of data and tag the data with additional metadata. Move only the data you need and manage the lifecycle of unstructured data intelligently.
Watch the unstructured data management workflow with Komprise CTO and co-founder at Cloud Field Day.
Related Terms
Getting Started with Komprise:
- Learn about Intelligent Data Management
- Schedule a demonstration with our team
- Read the latest State of Unstructured Data Management Report
