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We work in a market in which 'now' is not soon enough and the volume of information is proving to be both a blessing and a curse. How we manage our data is a quandary that still vexes many organisations faced with rapid data expansion.

Most organisations are becoming acutely aware of the four V's (veracity, velocity, volume and variety) and the potential that might lay dormant in their own data. Logical Data Warehouse, Data Hubs and Lakes are emerging as the grapple continues to consolidate, organise and consume data to leverage any competitive value that sits deep within their own unique slices of information.

Typically NoSQL databases such as MongoDB are proving key in helping organisations begin the process of consolidation and data exploitation. Managing Big Data may be big business but it is also proving too complex and expensive for many who are struggling to take advantage of the potential gold mines of insight residing, well… somewhere!

Whatever the combination of applications or systems deployed there will invariably be a database of some flavour containing information that is vital to the running of a business. Mostly these will be relational (RDBMS's) such as SQL Server, Oracle, MySQL or DB2. These are the systems many organisations invested heavily in to run their on-line presence or back-office functions but they seldom meet all the departmental business needs.

POP CULTURE
The by-product is that it is not uncommon to find 'popcorn' applications and systems within departments. These are small systems that pop up to meet a specific need of a localised business function that was either unplanned, appeared through changes in goals or was de-scoped from a project only to reappear wearing a different mask. Data audits undertaken at the majority of businesses tend to discover feral database installations. As a consequence data consolidation can become a tricky exercise if there are multiple versions of unregulated or unmanaged data elements.

The control that many data owners thought they once had, and would prefer to have, is often highly diluted or sometimes even absent. The reality is, not all organisations actually have the skills, expertise or resources to regain control. Some may even struggle to manage their core database landscape due to its sheer complexity.

VARIED AND COMPLEX
Most organisations have database software and storage of some description, a need for administration services, performance tuning exercises, taking of backups, maintaining high-availability, ensuring SLA's and business contingency expectations are met and not least, that security protocols are adhered to.

All of these processes and functions come at a cost. The sheer variety, value and complexity of databases is always going to be challenging for any CIO's budget even when there is a preferred vendor policy in place (and sometimes because there is a preferred vendor policy in place).

It is essential that each database, and the data inside, be given the support and protection it needs. And whilst popcorn applications may have smaller data sets they may contain sensitive data or data that requires integrating into your 'Big Data' sets and protecting just as vigorously.

DATA TO THE FORE
With operational costs very much at the forefront of business thinking, many have turned to the Cloud to simplify their data management needs. You only have to look at the exponential rise of IaaS, SaaS, PaaS and AaaS just by way of an example.

With that in mind, it's unsurprising that many extreme data users such as universities and research establishments are looking to the Cloud for answers to data related questions. This in turn has inevitably prompted the recent notable rise in the interest surrounding Data-as-a-Service (DaaS).

DaaS presents the opportunity to take advantage of everything we've grown to expect from a Cloud service: access to expert-level skills, reduced licence costs, efficient administration and assistance in consolidation, data architecture and procurement. Digital business demands an online presence with little allowance for downtime or loss of service. An increase in agile development and implementation processes across the development life-cycle are demanding there be equally agile support processes.

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