By Josh Good, Director of Product Marketing, Qlik

If “a week is a long time in politics” then it must be worth an eon in world of enterprise IT. Another day and another ‘Anything-as-a-Service’ cloud offering popping up to provide a new competitive advantage for beleaguered CIOs.

And while it’s easy for a lot to get lost in the noise of the on demand movement - we shouldn’t underestimate the impact this technology has had in readdressing the balance of power between new and established businesses.

Data-as-a-Service (DaaS) is the latest and greatest in a long line of these new IT models. While every business understands that data, and the insights that can be gleaned from it, are vital, it can be somewhat overwhelming for smaller organizations trying to contend with large volumes of scattered and often unstructured information (better known as Big Data). It’s no secret that big data requires big investments to make it work. Capturing data and storing it securely are costly endeavours - and that’s before we even reach the analysis stage.

Of course there are more concerns than simply rising costs. Issues over data security, version control and administration are all obstacles to smaller organisations owning potentially valuable data sets.

Data Alone is Not the Answer

While data is undoubtedly crucial to most, if not all, organizations, there is an increasingly prevalent myth that data is the differentiator. The perception seems to be that the more information an organization can lay its hands on then the more equipped it will be in gaining an advantage over the competition. This is a simplistic view: data alone does not provide a competitive edge, data insights do.

Not all information is born equal. While some data sets are inherently valuable – a database of customer prospects or sales leads, for example – many data sets are not, in themselves, all that useful. In fact, users often find they need more context around their data in order to get the insights they seek. Business rarely goes on without external influence; therefore external sources are often required to gain a clear view of what is happening within the enterprise.

The good news is that information is now freely available, perhaps gathered as a matter of process or from open data sets or can be cheaply purchased. However these sources are not always easy to integrate or leverage correctly. As the costs and complexity of managing multiple data stores becomes increasingly apparent, we can expect to see a rise in the number of organization outsourcing the collection and management of their less important data sets. After all, the data itself means nothing if the organization is too busy tracking down information rather than extracting insights from it. We would not expect a gardener to build his or her own tools; instead we accept that while they have the same equipment as a competitor, it is the skill they bring in using these tools which sets them apart.

Outsourcing Data Worries

The on-demand availability of normalized data sources that users can quickly pull in for added insights can be a decisive factor in making more informed decisions and helping a business make the most of their market opportunities. Organizations can use this data to augment and cross reference their internal data to gain greater contextual understanding and drive deeper insights.

The potential benefits are limitless. A sales manager could add population data to sales data to better understand market penetration or combine weather information to understand the effect of weather on retail sales. An organization can look at economic data to predict their own growth patterns within the region or consult demographic data to plan potential expansions into new cities, countries or continents.

Critically, Data-as-a-Service is not going to be a short-lived phenomenon. With the importance of data becoming more widely understood organizations will be looking at the most efficient way to take advantage of this trend. Owning smaller volumes of data and keeping it safe and secure, while outsourcing more general information is the best route forward. This way concerns over the cost and complexity of data generation and storage are taken out of the equation – meaning that start-ups can compete with their larger rivals.