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Talking to some C-level executives and BI experts across the USA, it struck me how Big Data is seen as a great opportunity, but also met with quite a bit of hesitance. “I love it in concept, but I’m not sure it’s for us, right now”. For years, companies have been trying to become better at Business Intelligence, make better use of their internal data, create better insights to base their decisions or provide more people with ‘self-serve’ access to data. In private, off the record, IT executives admit they’ve been struggling at it. Business Intelligence has ended up on the wish-list between the many important priorities of IT, the budget pressure, the demands to address mobile, virtualize the datacenters and desktops, move to the cloud, address social media, necessary migrations and upgrades, implement voip and video conferencing, increase security, think about Bring-your-own device etc. etc. And these are just the technology related innovations. I’m not even talking about the great industry transformations that are happening in finance, healthcare, education etc., each with their own impact on systems and information.
Perhaps for some companies, it’s a matter of walk before trying to run. First get better at using existing, internal, low-volume, fairly structured data sources before trying to tap into the fire-hose that is big data. Current business BI users, who love a simple report or dashboard, aren’t necessarily looking to give up those tools, even though Big Data may promise more and better insights.
And while one view is it can’t hurt to just start a pilot of some sort with big data, some true BI experts I spoke to shivered at the thought of collecting and storing terabytes of data without a proper plan. They know: once the business gets hooked on something, it’s hard or impossible to touch it, to redesign it, to revisit the model. For example, once the marketing team has seen sentiment tracking linked to sales figures, that pilot system is there to stay. One CIO even regretted starting a pilot at all, because after the pilot, everyone quickly retreated into familiar territory, instead of embracing the bigger change that is still ahead.
So, while the concept and insights of Big Data are increasingly clear, the actual organizational change that comes with it, may keep companies from effectively using it for quite some time. Agree?
Is it still too early for Big Data?
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Almost agree.
If you mean the actual organizational change includes the hiring of analysts that know their K-Nearest Neigbour from their Neural Network algorithm (data scientist) then I agree. Don’t forget this highly hyped phenomenon adds to the already difficult world of “Well organized Business Intelligence”.
For some, multinationals, banks, insurance etc., it’s a nice playground where analysts can test if extra data adds to the available information.
Others wait until types of Big Data analysis becomes a service they can purchase, like with Coosto.
Big Data is not for everybody, at least not to do themselves.
@frank: Hiring (or creating) ‘data scientists’ is only one thing, it’s also rethinking how you make decisions and what kind of culture you have (data or intuition?) etc.
I think you phrase it well when you say that it ‘adds to the already difficult world of “Well organized Business Intelligence”’: to organize Business Intelligence well is already quite something. Perhaps the question is if Big Data needs that as a basis, or that Big Data is something different altogether, that could be done separately or in parallel.
So how do we approach/educate our customers to embrace Big Data without creating that sense of fear, uncertainty and doubt. Are we moving too fast.
The data explosion, deluge or whatever you would like to call it is a fact. “Big Data” is exactly the same kind of catalyst that “Big Science” was and still is. “Big science is here to stay,” Alvin Weinberg wrote in 1961. Now, some 50 years later, the same goes for “Big Data” and there will be just another next phase of course. Remember the title of Derek de Solla Price’s book “Big Science, Little Science . . . and beyond.” In 1986 it was a mere extension of Derek’s 1963 publication that back then lacked the last two words. Conclusion: it is never too late or too early for the next big thing. Calling something “big” is a cry for attention to start with, hoping discussion will follow.
I agree with Frank above and Jaap’s sentiments. I think in Health, Medicine and Environment it is never too early. I think in Business particularly Finance then maybe too early. However, with FATCA, Anti Moneylaundering with their Know Your Client dependency much of the data is in the 80 to 90% of unavailable (without Big Data capability) unstructured data. I think a good place to start is engaging Cloud services with native or propriety Hadoop clusters for archive data (dark data) to crystalize a data retention policy. Build up the confidence and expertise at pace but controlled pace expanding functionality step by innovative step.