The promise is timely access to essential business insight; the reality is a massive dent in the CFO’s budget. So why are organisations still investing in projects for Big Data Analytics for Business? For any CFO concerned about throwing good money after bad on big data deployments that are simply failing to deliver the information the business needs, there are three essential questions to ask. Why does the business need to collect this data? How is it going to provide value? And, critically, if the way IT has attempted to manage big data to date has not succeeded, isn’t there a better way?
Big data is dominating the CFO’s agenda with CIO’s requesting ever-increasing budgets to keep pace with the technological challenges of managing ballooning volumes of data. But how does a CFO measure the value from this additional IT spend?
The situation is set to get worse. While the vast majority of CIOs have yet to wrestle control over structured data and deliver the insight required to drive operational improvements, Forrester Research estimates that over 45% of big data deployments are now for marketing. Once again, the CFO is being asked to pile even more investment into the big data project. But is this simply a case of throwing good money after bad?
Calling Time on Big Data Analytics for Business
And the problem is not new. Organisations have been struggling to come to terms with growing data volumes for years. Despite the continuing advances in technology – often expensive, leading edge technology – the problem just doesn’t seem to want to go away.
Organisations always seem to have too much data to analyse and not enough computing power to do it in a reasonable timeframe. This is because there are fundamentally two problems with this approach; Organisations are trying to collect the data from too many sources – often without good cause and the result is an entry-level investment point far beyond the budget of all but the largest organisations and a technology model that is simply not fit for purpose.
So where next for the CFO’s big data budget?
Realising Data Value
The relational database (RDBMS) has a place and a purpose, but it is not a tool that was ever designed for the data volumes it is now being asked to handle. Despite upgrades, add-ons and a vast array of clever engineers, when it comes to big data, the RDBMS may well have had its day.
Working in parallel with today’s operational systems and existing data warehouses, the latest generation of in-memory database services and database technology requires just a server, not an entire data centre, to run. Exploiting innovation in areas such as data compression and pattern matching, these solutions require not only minimal infrastructure – and hence cost – but deliver a new way of locating information within the mass of data to enable rapid response to critical business questions.
There is nothing wrong with the concept of turning big data into valuable information for businesses in the retail, insurance and logistics sectors. The problem has been the way the IT industry has attempted to achieve this goal. It is time to accept that attempting to manage fast escalating big data volumes with a traditional RDBMS does not work. But is the CFO brave enough to demand that IT takes a step back, explores the latest innovative tools and techniques for managing data and makes a small but justifiable investment that has a real chance of delivering a return?
Want to take the next step into Big Data science and start getting value from your business data? Contact us today and we will help your business to thrive using Big Data to your advantage.
Zizo: Specialists in Big Data Analytics for Business.