What Affects The Value Of Big Data?
Raw data in itself is worthless. Even more, raw data in itself just means costs. Costs related to storing and processing that data. Only when that data is analysed, insights can be derived from it and value is created. These insights determine the value of big data. Of course, organisations that want to develop a big data strategy also want to pre-determine the expected value. Value from big data can be achieved by building comprehensive profiles that will give organisations insights and the ability to target customers very precisely. But obviously there are many other big data use cases that provide all kinds of value from big data in any industry around the world. The problem however is that any possible value is affected by many different variables.
For example, the way the data is presented influences the value. Big data that is available to consumers and employees at any moment, anywhere at any device is of course more valuable than data that gives insights just once a week via your desktop computer. On-the-go big data as I call this, does require a different approach in presenting data as discussed earlier but also in the way of dealing with the data storage. Robin Kuepers, Enterprise Marketing Director Western European Region at Dell, foresees that in order to take full advantage of the big data, the total data storage architecture solution should include data created and stored on mobile devices.
Also how the data is secured affects the value derived from it. Of course, the better secured the better it is. With the ‘Bring Your Own Device” trend appearing around the world, this could get a completely new meaning. Companies have to ensure that all different devices with different operating systems and different models are all secured correctly. This could be rather expensive. Especially with mobile devices, securing the data is extremely important. Kuepers therefore foresees that in the future there will be a virtualization layer made possible on the mobile devices. As is already possible on desktops or servers where you can use different operating systems on the same device. This mobile virtualization will greatly improve the security possibilities on mobile devices and thus increase the value derived from on-the-go big data.
With the growing amount of data created on a daily basis, the storage will also become very important to take into account when developing a big data strategy. The right storage decisions can save a lot of money in the future. Storing the right data, at the right moment in the right way should become part of a big data strategy as it can deliver a lot of value in the future. Of course there are many possibilities and all having their advantages and disadvantages. Kuepers sees a trend in the direction of “cheap & deep” storage; for the same price less features but more storage space. With the explosion in data weighing the different options becomes more and more important.
Finally, also the technology impacts the value. Organisations can opt for open source tools, enterprise solutions or an “all-inclusive” solution. With the growing amount of big data startup that specializes in one aspect of the big data field, a lot of insights can be gained. The problem is however that in the end it could lead to a plethora of different applications within the organisation. On the other side of the spectrum there is the all-inclusive solutions, primarily delivered by large organisations for large corporates. Of course, with a big data strategy that is implemented throughout the organisation, having only one supplier to deal with could be cost-effective but also lead to many processes that have to be followed.
The value of big data is of course in the insights that can be derived from combining and analysing (different) data streams. How all data is store, how the insights are derived and from where the insights are accessible does have a big effect on the total return in the end. Organisations therefore will have to think carefully and plan ahead when rolling out their big data strategy and take these important aspects into consideration.