Tackle Big Data with File Analysis

The Problem with Big Data

Few organisations have the resources and time to manually manage and maintain the “Information Lifecycle” of data within their organisations, whilst also planning for future data growth.

Simply adding more storage capacity every time capacity is exceeded only compounds the infrastructure management burdens, creating potential points of failure, and consuming precious IT resources and budgets.

The seamless and continual operation of many business depends on the availability, performance and capacity of the information infrastructure. As the business and IT environment grows, it becomes all too easy for the storage of data to become disorganised, generally unhealthy and unmanaged.

In our experience, an average 32% of an organisation's unstructured data can be classified as Redundant, Obsolete or Trivial (ROT), this unnecessary data consumes increasing and avoidable amounts of storage and management costs.

The Solution starts with File Analysis

File Analysis, powered by HPE Storage Optimizer, is our Oyster IMS' pioneering service to help you understand and control your growing information; and to improve ongoing information management.

Our File Analysis service provides a detailed analysis and report, focused upon a data sample representative (up to 1TB) of an organisation’s unstructured dataset. The findings from this analysis will provide an invaluable insight into the level of data file duplication, individual data file size/aging characteristics and the immediate identification of data files with zero value (enable the initial steps into the creation of a data disposition and data management strategy).

File Analysis provides a detailed analysis and report, focused upon a representative data sample of an organisation’s unstructured data.

The findings from this analysis will provide an invaluable insight into the level of data file duplication, individual data file size/aging characteristics and the immediate identification of data files with zero value (enabling the initial steps into the creation of a data disposition and data management strategy).

File Analysis: the Deliverables

1. A ROT analysis of your unstructured Information.
This analysis will immediately identify areas of cost savings:
- Redundant Data: files that contain identical content (duplicate data files).
- Obsolete Data : file contents have not been accessed for multiple years
- Trivial Data: classified as not company-related (defined per organisation).

2. Valuable insights
See how backup time can be reduced with intelligent archiving and stubbing.

3. An immediate snapshot
Insights into the data you have and what could be defensibly disposed.

4. Infrastructure recommendations
Based upon the analysis of the sampled data.

File Analysis – ROT identification

File analysis ROT report

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Gartner says:

" Storage managers, legal and security professionals, and business analysts are seeking ways to manage unstructured data stores to reduce costs and risk, and increase efficiency of valuable business-critical data. File analysis enables better information management decisions for unstructured data."

" Explosive, unstructured data growth is forcing IT leaders to rethink data management. IT, data and storage managers use file analysis to deliver insight into information about the data, enabling better management and governance to improve business value, reduce risk and lower management cost."