Data Classification

To address the spiraling challenge of managing data growth, organisations are looking for technologies and practices to both reduce storage costs and introduce more efficient data management strategies.

Data Growth is a challenge faced by almost every organisation, typically caused by the perception of cheap disk coupled with the tendency to retain all data for compliance and big data initiatives. The challenge is magnified with increasing complexity in the data with up to 80% being unstructured, dispersed over multiple infrastructures and requiring complex management practices.

In response to the spiraling costs of managing this data growth, organisations are looking for technologies and practices to both reduce storage costs and introduce more efficient data management strategies. The most effective way of evaluating future options is to gain full visibility and understanding of the data through a Data Classification exercise that quantifies data sets in terms of business value and derives appropriate corporate policies for managing data as it ages through its natural lifecycle. These policies can then drive requirements for online storage, data protection, security, collaboration and governance and can be used to define service catalogues and appropriate infrastructures.

Classificatin

 

4sl have developed and delivered a Data Classification service based on a thorough analysis of all aspects of data management and focussed on evaluating data from the perspective of its value to the business. It is built around a three pronged approach of classifying data and applications, formulating data governance policies and proposing a data architecture.

It initially involves capturing information on a number of data points including:

  • An analysis of Applications in terms of their Business Role, Data Value and Criticality.
  • Deep insight into various data sources, in particular unstructured data and file repositories, what it represents and what business users do with it.
  • Capturing any data regulations in terms of security, location and data retention.
  • Reviewing existing Storage and Backup Architectures to gain an understanding on how data is stored and protected.
  • Capturing requirements and use case scenarios for eDiscovery and the need for a fast and efficient search capability.

A combination of workshops with key stakeholders and business users and automated data capture is used to gather and process information.

With large volume of unstructured data in particular, 4sl will execute data analytics software to get an appreciation of data value in terms of age and frequency of access.

Focussed dialogue is required with key stakeholders and business departments to gain an understanding of who creates the data, who is responsible for it, who should have access and how it is used for collaboration. Pre-Defined Questionnaires are completed and a data flow is derived for each department.

For structured data, 4sl will assess the business value of key databases, capturing and defining their availability and protection requirements.

The key outputs from the Data Classification phase are:

  • A Data Governance Policy containing the definition of a Data Lifecycle from creation through to disposal and defined retention periods for different data categories.
  • Storage and Backup Strategies defining service catalogues for storage and backup services. This will identify requirements for tiered services and introduction of new technologies and associated transformations.
  • Data Security requirements in terms of overall information security, access control and sensitive data management.

The third prong of the Data Classification Service is mapping the Data Governance Policies, Storage and Backup Strategies and Security Requirements to an overall Data Architecture consisting of technology blueprints to be evaluated by the client. These technology blueprints can encompass:

  • Specifications for archiving solutions required to automate data governance policies.
  • Architecture blueprints for storage and backup solutions, encompassing new technologies and capabilities.
  • Security standards and potential technologies for access control, compliance monitoring and sensitive data management.