Organizations need to evolve their data management strategy
IDC predicts that over the next five years, more than 80% of data collected by organizations will be unstructured data, and that this will only continue to grow by 40-50% per year for most companies.
With the sheer volume of unstructured data yet to be created and used in the years to come, it’s safe to say that the way organizations manage their data will need to evolve.
Eric Burgener, vice president of research in IDC’s infrastructure systems, platforms, and technology group, wrote an IDC insight note.
In the brief, Burgener urges organizations to implement a comprehensive data management strategy to deal with this growing influx of data, noting that a data mobility engine forms the basis of a data management strategy. efficient data and can generate significant benefits for the hybrid multicloud enterprise.
“A good [data management] takes into account not only the heterogeneity of storage in most enterprises, but also a number of other areas, including onsite and offsite deployment models, application availability, data integrity, security , compliance and regulatory needs, efficient use of resources, and the fact that more than 80% of data created in the next five years will be unstructured (i.e. file and object based) writes Burgener.
Five Core Components of an Effective Data Mobility Engine
1. Vendor Independent Interoperability
The data mobility engine should focus on data, not systems, and be able to move data between different types of systems as well as cloud targets. Both file (NFS, SMB) and object (S3) access methods should be supported, preferably in a multi-protocol fashion to support efficient capacity utilization when data needs to be shared between different types of apps.
2. Knowledge and Information
The data mobility engine must provide visibility into the data metrics, access patterns, and usage activities that can serve as the basis for classification, and this visibility must be comprehensive. It should also include AI-based intelligence that can analyze these metrics to make policy recommendations that drive an effective data management strategy around storage location, data protection, security, compliance, migration, and ultimately reducing storage costs. With more comprehensive metrics, data residency can be managed to ensure data is kept in the “best” location (given business objectives) and stale data is identified and deleted.
3. Orchestration and Automation
With the complexity of today’s multi-site IT infrastructures, monitoring data usage and compliance and manually managing data classification and migration are risky propositions. Automation improves the speed and reliability of operations while improving administrative productivity, increasing the scope of administrative control to reduce costs.
4. Scan, optimize and copy capabilities
All these operations must be global in nature. Scan provides visibility into data and its usage, collecting the metrics needed to intelligently find and manage data. Delta differentials, compression, and other storage efficiency technologies maximize resource utilization when moving and storing data, allowing operations to be performed as quickly as possible. The copy includes replication capabilities, which can further help optimize data migration to create the most efficient data placement strategy.
5. Applying Integrity
The data mobility engine must support data integrity during all operations. File-level and object-level verification must go beyond simple TCP checksums to detect and correct silent data corruption using “before” and “after” hash comparisons, a string control and advanced integrity protection (regular inspection of the destination content to detect possible changes that conflict with the source).
Implement an effective data management strategy
As more companies re-evaluate their unstructured data storage needs to cope with the increasing amounts of human and machine generated data, most companies are looking for a viable solution when it comes to data storage. to execute a comprehensive data management strategy, Burgener’s report reveals.
Over the past few years, more and more IT managers have wondered about data classification, data visibility, and organization-wide data accessibility, as well as how to manage data. and high costs resulting from a fragmented data management strategy.
These IT decision makers understand that the future is changing for their data, with many already storing petabytes of data that will continue to grow in years to come, but they are hesitant to change how that data is stored and protected. . Their on-premises solution is a “comfort zone,” so to speak, and the thought of moving all those assets to a new platform is daunting.
Finally, Burgener states in its report that “benefits of an effective data management strategy include reduced IT costs, easier data sharing, better security, less legal exposure, and better ability to demonstrate governance. and regulatory compliance”.