One of the most obvious opportunities for CIOs to run a more efficient data management infrastructure is to address the issue of storage tiers. Commonly, secondary storage is not efficiently utilised. The data assigned to secondary platforms tends to be stored to the media without a second thought, whereas the primary storage space, which is perceived as more expensive, is generally better managed with the data tiered according to priority.
Organisations that are serious about implementing analytics processes should make it a priority to establish a data management policy that categorises where, and on what platform, data will be stored, thereby slashing costs. There are now more choices for secondary storage platforms. Cloud storage, for example, is becoming an increasingly viable secondary storage option that provides similar advantages to tape, in terms of cost-efficiency, but with the easier data access that analytics processes will demand.
3. Improve skills
'Big data' and analytics trends are driving a rapidly changing industry and environment. A recent IDC study sponsored by CommVault reveals that for IT departments across the region, maintaining the human resource with skills to keep up with this change is a key concern.
In order for data analytics to be successful, CIOs should expect to make decisions related to human resources, or as McKinsey puts it, 'executive horsepower'. An efficient and effective data management policy is at the very core of a practical and profitable analytics program, but for companies pursuing the potential of data analytics, questions about IT leadership and skills are certain to arise as IT departments are confronted with new tasks to harness and exploit data. Decision makers must be prepared with a clear human resource strategy that has the capacity to meet the requirements of analytics ventures – whether this means the appointment of a Chief Analytics Officer, a Chief Data Officer, data scientists or simply expanding the team.
Modern analytics trends mean that data has the potential to be a huge corporate asset, offering value in predictive marketing and consumer insights, for example. However, CIOs interested in the promise of modern data analytics should first make sure that their departments are effectively able to 'walk' by implementing a modern data management strategy with sufficiently skilled teams, before 'running' with analytics and all that it can potentially offer.
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