Enterprise Cloud Adoption

Optimising the Data Lifecylcle

An approach to managing data across its lifecycle, from collection and use through to obsolescence.

Businesses strive to obtain greater value from analysis of exponentially growing and increasingly diverse data estates. Minimising the costs and risks associated with maintaining inactive, expired, duplicate or irrelevant data makes strong commercial sense.

More than half of all the data held by companies has an unknown value, and around a third is estimated to have no value at all. Understanding the cycle of data usefulness is critical to optimising the return on data investments in your business.

The data lifecycle follows the 5 key stages:

  1. collect – data gathered from a range of sources comes under the remit of corporate data governance. Rapid evaluation of data allows a reasonable proportion to be discarded, reducing the associated cost and risk.
  2. store – data is accumulated for immediate and/or future use using the most effective technologies, to avoid data duplication and exploit virtualisation techniques as well as to automate storage tiering. This enables significant storage cost savings.
  3. use – stored data is referenced or processed for one or more business application, development or testing purpose. Just-in-time provisioning and data quality management minimises errors and optimises value generation.
  4. expire – the business value of data depreciates over time, so appropriate archival or deletion has a direct impact on minimising cost and risk.
  5. erase – for security, compliance and cost reasons, it is important to comprehensively and safely eradicate data which has no value.

ECS investigates each lifecycle stage for the selected data estates and makes clear recommendations on how best to reduce cost and risk and maximise ROI.

ECS focuses delivery around key outcomes, including:

  • a profile of the costs, risks and values against each of the lifecycle stages
  • optimal configurations for in‑scope data across each of the lifecycle stages
  • a set of recommendations for each lifecycle stage to reduce the costs and risks involved
  • any opportunities for other data uses to increase overall data value
  • a report on data governance and reporting
  • a set of clear technology recommendations, and the benefits these should deliver.

Benefits of this approach include:

  • a clearer understanding of the cost, risk and value profile of in-scope data
  • greatly improved, bespoke data governance
  • a lifecycle perspective in a catalogue of in‑scope data elements
  •  reduced risks, lower costs and increased business value

It is also important to ensure that effective data lifecycle management is not restricted to production data.

Over 80% of the overall data footprint, and 60% of the data risk, happens at the development or testing stages.

ECS works with you to optimise the return on data investments. When applied in conjunction with test data management, a significant increase in value can be gained across the test data estates.