Christian Prokopp, PhD, is a Principal Consultant at Big Data Partnership in London developing big data strategies, architectures and products for clients. Previously, Christian worked as a big data architect and senior data scientist at Rangespan, a wholesales E-commerce analytics platform, where he built a large scale cloud based data mining infrastructure and processes until a successful exit (Google acquired the company). He loves traveling and spent the last one and a half decades finding excuses to live, research and work on three continents hoping to make it six eventually. His professional interest has always been information technology and how to push its boundaries to achieve better business outcomes. He therefore can be found discussing big data strategies with CxOs as likely as diving into technical conversations with engineers and data scientists. Christian tweets as @prokopp and spends his spare time as a blogger, (ghost) writer and speaker.
I recently wrote an article about how to get a Big Data initiative back on track. In the comments section, a user challenged how such an initiative is different to a traditional analytics project. That’s a good question, and the answer is not immediately obvious to most. The key differentiators are not Hadoop, NoSQL, large datasets or any of the usual suspects. The difference is that it is impacting all organizational datasets, the overall flow of data in the long-term, as well as data processing and storage.
In this year’s Gartner hype cycle analysis, big data is approaching the trough of disillusionment. Does that mean it is unlikely for organizations to succeed with big data adoptions and should they focus elsewhere? No, of course not. Marketing has done its job and everybody has heard of big data, though few know what it means for their organization and how to approach the topic. Yet, the answer to how to succeed with big data is surprisingly straightforward once we ignore the hype and focus back on the basics.
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