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Thore Rabe, vice-president EMC Isilon EMEA, examines what needs to happen for big data to reach a tipping point.
For the past five or so years there has been a considerable amount of hype around the ‘big data revolution’. However, as any vendor can tell you, many businesses are still some way from truly seeing the benefits and value of big data projects. For many, the goal of being able to connect and analyse vast amounts of data from daily life and use key insights to improve products and/or services still remains a dream.
This is not down to a lack of data. Ever since we first started hearing about big data, the volume and variety of data available to businesses for analysis has grown exponentially. Today data flows from phones and credit cards, televisions and computers, the infrastructure of cities or sensor-equipped buildings, trains, buses, planes, bridges, and factories; and much more. Organisations across all sectors therefore have multiple data sources to select from and use to their advantage.
However, when it comes to organising and making sense of this data, many businesses don’t always know where to start – an inertia often seen with the advent of new technology trends.  The beauty of big data projects is that businesses don’t always know where they will take them, or even what the desired outcome is. That is the power of big data – the ability to discover insights that no one knew were there – but it also makes things difficult for businesses inexperienced in the technology.
To help such organisations make a start with their big data projects, it is now clear that the IT industry must work with customers to give them more confidence and support. By offering organisations the right mix of people, technology solutions and processes on the other hand, the industry can help them realise their big data dreams much more rapidly and effectively.
There are three critical points that must be addressed if big data is to deliver for businesses: people, TCO modelling and leadership.

As with any project, big data will only live up to expectations if the right people are in place. This means that businesses must expand their big data conversations well beyond the IT team and open them out to other business stakeholders, such as marketing, business development, finance and the relevant board members. Business units that have the vision to see projects through and realise the wider business benefits they can bring are the best to target.
Some telecoms operators, for example, are using big data analytics to monitor customer behaviour; collecting location- and time-based data from consumers’ mobile phones when they opt-in to the process. This means operators can detect the number of visitors to certain attractions, shopping malls or pedestrian zones and the busiest times of day. The operators can then sell this valuable information to retailers, media companies and tourist attractions, so they can better target customers with location-based promotions at the right time to increase sales.
Clearly, the people involved in such projects must recognise the potential value of the data they hold. Moreover, whoever leads the project must be able to navigate across different business functions and moderate decisions appropriately. Sometimes, external consultants can play a positive role to help mediate the process.
The key to success is to ensure buy-in from right across the business from the outset of the big data project. Otherwise the project risks being viewed as a fancy add-on or nice-to-have, rather than something that will deliver real value throughout the business.

TCO modelling
Secondly, accurately defining the Total Cost of Ownership (TCO) is an essential first step to any big data project. In fact, in an ESG Lab Review this was outlined as one of the most important considerations for businesses when looking at big data, analytics and business intelligence technology.
Calculating the financial cost of these projects involves assessing and investing in the right technology and skill set combinations, understanding which technology is most efficient for which workloads and engineering an ecosystem that allows the selected technologies to work well together.
This approach will help organisations make better choices over the right technology for the problem(s) they want to solve and it is something that their vendor partners can help them understand. Without TCO, the ultimate value of big data across the business will not be realised and the project will be doomed to fail.

Finally, businesses should look to ensure a senior business sponsor or Chief Data Officer (CDO) is in place to help steer the initiative across the business. Working alongside other C-level executives, they will help reshape the business as it undergoes the digital transformation that big data is both a part of and further engenders. Given that many departments are often involved in these projects, it’s the job of the CDO to ensure the data and insights gleaned don’t sit in siloes. They should try to build a joined up approach to data and knowledge sharing.
Ultimately, organisations that approach big data from a value perspective and involve senior business decision makers across the business as well as IT are much more likely to be successful than those which adopt a purely technology based approach. It is a mature approach to big data that will hopefully see the technology reach tipping point sooner rather than later.