Friday, May 23, 2014

Is Big Data for Everyone?

Fit-for-Purpose approach is the right way in Big Data initiatives. 

Big Data does impact everyone’s life, hence, there are all the bells, hype and whistles. However, it doesn’t mean every business must pour the huge amount of resource into it. The Big Data question is ultimately- what is the ROI? Some companies can say right now that for them, it's great, and they're happy. In general, it seems businesses are best in an evaluative repose. It's all about "show me the value!". And it is tactical that each company must evaluate the ROI for their company on Big Data projects.

Fit- for-Purpose approach. Any big data or data initiative must start with a clearly articulated business purpose. That purpose must be rooted in cost avoidance or revenue increase. There must be a path to operationalize the analytic as well and that is where people and process are in play. Big Data success is beyond a POV or POC project and is rooted in real business value which can be implemented in a timeline that can show the value. Otherwise it is a science project. The fact is, much like Cloud, big data technologies are ready for tactical applications and are delivering real value. They aren't right for every job of course, which is why firms are adopting a Fit-For-Purpose approach.

Big Data is much more than just Hadoop. It is a common mistake to equate the two concept. Second, Hadoop is not "a platform of files", but a distributed file system that stores data on commodity machines, providing high aggregate bandwidth across cluster, and it has a massively parallel processing system that understands a programmatic approach to working with data. The reality is that these technologies are here, being well utilized, and are going to cause a permanent change on how you design and architect solution going forward. Just implementing a Hadoop infrastructure doesn’t mean that anything valuable is being done on it. The ability now available to capture structured and unstructured data from any source will enable big data results. And more business will spring up to enable the utilization of big data. It is also a mistake to think these technologies are only useful in large data sizes. Most projects start with modest data sizes with the flexibility, or scale of compute is the driver rather than data size.

It is not a "binary" considerationIn general, people are not very good at being neutral, or objective. So with Big Data, some people tend to polarize - move towards the extremes. Some think that Big Data will be for everyone and every industry that is the reason for the hype; others think Big Data is just a fad, would fade away soon. The point is Big Data does affect everyone’s life, however, you do not have to analyze your data requirements up front to be impacted by or get impact from big data.

Therefore, focus on the value proposition of Big Data. Big Data, the term, may be overused or over-hyped. But what it represents is real and impacts everyone, whether they want it to or not. Those who choose to believe that big data is not relevant to them simply will not be competitive when moving forward. The key to maximizing deployment success is to understand where you're headed with your data, and taking a disciplined approach to investing in an understanding of your true data needs first. Keep in mind, Big Data is means to the end, not the end.


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