Research shows that 80-90% of all enterprise data falls into the category of unstructured data, consisting of everything from documents, video files, email archives and application specific data types. Most organisations overlook the need for an unstructured data management solution that helps turn this data from a cost center into a strategic asset.
The problem looks like a storage issue, which is easily solved by buying more storage. But the challenge isn’t just storage capacity. Companies need to think about data management solutions that give visibility, control, and operational intelligence across their data estate. The right solution will help organisations reduce costs, improve productivity, and support business growth.
Why do you need Unstructured Data Management
Unstructured data is both a cost, a risk and an opportunity for businesses. Without proper management they will face:
- Operational inefficiency: Users spending up to 30% of their time searching for the right data
- Runaway costs: Unmanaged data growth from users means over-provisioning of storage by IT teams
- Compliance exposure: No knowledge of some data means that data with regulatory requirements is likely not being managed
- Security vulnerabilities: The sprawl of data locations mean inevitable blind spots for security teams
Organisations who implement effective unstructured data management solutions immediately see improvements in operational efficiency, cost management, and risk mitigation.
Essential Capabilities of an Unstructured Data Management Solution
Data Discovery and Analytics
An unstructured data management solution should give visibility across all storage classes, platforms and locations. It should perform fast, non-invasive scanning to index large amounts of unstructured data without impacting storage performance or triggering cloud retrieval costs.
Requirements should include:
- Multiple storage class support including NFS, SMB, object storage, and all major SaaS storage platforms (Box, OneDrive, Dropbox, etc)
- Real-time analytics of storage usage, cost trends, and usage patterns
- Ability to group physical storage types in more a logical business view, such as by department, location, or project
- Identification of redundant, obsolete, and trivial (ROT) data
Visibility forms the foundation for data management activities and lets data owners make informed decisions about data placement and retention policies.
Data Movement and Migration
Data mobility solutions need to be flexible to let organisations transfer between any storage class or platform. This must include filesystem-to-filesystem, filesystem-to-object, and object-to-object transfers without the need for complex scripting and tools to get the data to where it needs to be.
Capabilities should include:
- Cross-platform compatibility to avoid vendor specific limitations
- The ability to scale and cluster transfer agents for maximum transfer throughput
- Easy to configure conflict resolution to prevent data loss or overwrites
- A way to automate scheduling of migrations
- Built-in validation ensuring complete data integrity
Cost Modeling and Financial Control
Cost predictability is important for enterprise data management. The solution should give accurate and easy to understand cost modeling to let leadership, administrators and individual departments budget and make informed decisions based on real world costs.
Features should include:
- Custom price books to enable accurate internal chargebacks and showbacks of data at rest
- Cost modeling to show the exact transfer and storage costs before a data migration is performed
- Multi-cloud cost comparison and optimization recommendations
- Automated cost reporting and budget alerting
Governance and Enterprise-Grade Security
Security and compliance is key with systems and interfaces that manage business critical data. Nowadays, access controls and audit capabilities are the table stakes for all enterprise applications and that is true of Unstructured Data Management Solutions.
Capabilities must include:
- Role-based access control (RBAC) with permission management
- Audit logging of all data access and transfer activity
- A metadata-only architecture to ensure that data never leaves the organisation’s control
- Single sign-on (SSO) integration with enterprise identity providers
Policy-Driven Automation
Manual data management processes are a good first step, but the Unstructured Data Management Solution should also support automated policies to make sure data placement, retention requirements, and compliance takes place automatically without manual intervention.
Automation capabilities should include:
- Storage tiering based on age, access patterns, or business rules
- Compliance-driven retention and deletion policies
- Support for workflow triggers based on metadata, time, or even business events
- Failure handling with automatic retry mechanisms and alerting
- The ability to integrate using APIs to embed into existing systems
Implementation Considerations for Enterprise Deployment
Scalability and Performance
The solution should have a track record of proven performance at enterprise scale and be able to reference customers who are managing multiple petabytes of data. The underlying architecture must be capable of handling large amounts of concurrent operations without affecting business operations.
Deployment Flexibility
The ability to deploy the Unstructured Data Management Solution in a way that aligns with an organisation’s policies and technical requirements. Both cloud-hosted SaaS solutions and on-premises deployments are a must.
Integration and Extensibility
The solution should integrate seamlessly with existing enterprise systems through APIs. REST API and Webhooks should be a minimum to let users integrate and build into wider business automation systems and processes.
Support and Service Level Agreements
The Unstructured Data Management Solution should be backed by a Support team with defined service level agreements. 24/7 technical support, regular health checks, and proactive monitoring are a must.
Measuring Success and Return on Investment
Implementing unstructured data management solutions lets organisations measure success of their buying decision across multiple dimensions:
Cost Reduction: ROT identification and intelligent storage tiering gives continually finance visibility that data is in the right place at the right time
Operational Efficiency: By reducing time spent finding and managing data, users have more time to carry out value creating activities
Risk Mitigation: Through enhanced compliance reporting and data governance
Scalability: Enabling businesses to grow efficiently without linear increases in storage and data management overheads
Conclusion
The right Unstructured data management solution will transform data from a liability that is sat on storage into a potentially value-creating asset. Organisations who evaluate solutions should make sure platforms deliver visibility, automation, cost controls, and enterprise-grade security.
Success needs more than point solutions or vendor-specific tools. It consists of an integrated platform capable of managing data across the entire lifecycle and supporting business growth.
By investing in a proper unstructured data management solution an organisation will see return their investment through reduced costs, improved productivity, and enhanced competitive positioning. Organisations who delay implementing unstructured data management solutions allow their competitors to gain an advantage of them in their market.