Looking back over 2013, the ‘big data’ era has certainly moved on. While the phrase has been around for a long time, there is no doubt that people have started taking it more seriously and looking at ways to take advantage of the huge business benefits it can bring. You only need to look at the likes of Facebook, Twitter and Google, who all acquired big data type companies, to realise this.

With huge amounts of valuable data being generated on a daily basis, from web and social interactions to shopping transactions, it’s not hard to see why. While big data has certainly got people’s attention, 2014 will be the year it’s catapulted to the forefront, but not without first sparking some debate. Here, we take a look at a few prominent contradictions to popular paradigms.

Hadoop’s synonymy with big data

Big data technologists, from producers to consumers, are beginning to realise the true value of integrating Hadoop into a big data infrastructure, which consists of other framework technologies to enable software-based architectures and data management services.

Indeed, the Strata big data conference bears testimony to this shift, as late as last year it joined forces with Hadoop World, and recently concluded its New York and Santa Clara conference. Ken Rudin, Facebook’s head of analytics, has even put forth this argument, stating that big data is not just a Hadoop framework, and that it could be a relational data store depending on the need in hand.

Many enterprises are evaluating their choices for the right big data infrastructure, weighing up whether or not to build their solutions on open source frameworks, like Hadoop, or proprietary ones, such as Teradata and Oracle. What is clear is that 2014 will be the year that many will realise that big data implementation needs more than just a Hadoop framework.

The big data supplier market will remain highly segmented

In 2014 there will be a clear difference between the approach of large enterprises and their smaller counterparts. The big data supplier market will find it is extremely hard to convince larger enterprises to go for their larger appliance box, especially if it already has very large data centres and infrastructure in place. When it comes to finding a complex and contemporary solution, such as this, a blend of online analytical processing (OLAP), online transaction processing (OLTP) and Hadoop offerings would be ideal and is more likely to define the market.

Big data technology suppliers, who have data management as their core business and the luxury of building applications for a wide variety of use-cases, will also be spending time on developing and perfecting proprietary frameworks and tools. On the other hand, smaller, or more niche, vendors will continue to emerge in areas like performance and scalability management, data access and querying, decision analytics, and visualisation.

While larger companies have the hours and resources to spend, smaller enterprises and independent software vendors (ISVs), are more likely to play around with open source tools so that they can adopt and reap the benefits much more quickly. Organisations of all sizes will therefore need to have a flexible approach when it comes to finding the right big data solution, not least because the big data supplier market will continue to remain highly segmented.

Big data solution focus around decision modelling

Data preparation was certainly a key trend last year, where the focus was to reduce the time analysing data and to create a much more scalable data model. However, it seems the focus will shift away from data preparation and towards decision making in 2014.

With huge amounts of data being generated from all avenues, businesses are under increasing pressure to analyse and contextualise this in a way that will increase revenue and provide a closer, more personal relationship with their customers.

As such, organisations will start focusing more on how to enable decision makers to make informed decisions quickly from large data sets, so as to create economic value across their workflows and function. This year we will therefore see more emphasis on visualisation and machine learning-enabled decisioning, compared to data modelling.

Shift in ownership of big data projects

CIOs used to own the majority of big data projects, as it was mostly considered a technology transformation and enterprise-wide data integration initiative. However, big data use-studies have proved its potential to generate business value across different organisational functions.

In 2014, more and more functional leaders, including CMOs, CFOs, CTOs and CCOs, will be demanding and owning big data projects. Unlike other CIO initiatives like, for example OSS/BSS, the return on investment (ROI) of big data projects is not only dependent on IT efficiency, but also on how data is consumed and analysed to gain insight for decision making and value creation. As functional leaders begin to realise this, they will look forward to playing a bigger role in the planning and execution of big data projects.

Trends converge to one direction

These predictions encompass several big data technology trends to look out for in the year ahead – including the choice of big data infrastructures, the emerging role of decision scientists, a shift in project ownership and a continuing highly segmented market. Ultimately, they all point in one direction; organisations are gaining a better understanding of the true value big data analytics has to offer. Those who realise and act on this will subsequently have greater insight into data needed to have the right decisioning power for generating economic growth.

Prateek Kapadia

Prateek Kapadia


Prateek Kapadia is CTO of Flytxt.