At the Strata + Hadoop World conference a week or so ago in New York, there was a great talk by Ken Rudin, leader of the Facebook Analytics team. He gave his views on how to leverage Big data effectively to deliver the most impact. The core of his presentation were three commonly held beliefs that needed to be challenged. A summary of the presentation follows below.
Belief #1: Big Data = Hadoop
Hadoop is a technology – one of several in the burgeoning big data space. An effective big data approach must focus on business need, not the technology.
Big data analytics allows for deeper analysis on a lot more data and different types of analysis, not possible in traditional tools like relational databases. However, many business believe replacing their relational databases with Hadoop is an effective big data approach. The reality is very different and picking the wrong tool for the job is painful and expensive. A big data strategy will likely employ several technologies – big data platforms like Hadoop, traditional relational, as well as any other suitable technology for the task at hand.
Belief #2: Big Data gives you better, deeper answers
Big Data analytics does indeed allow for deeper insights, however coming up with answers to questions no one actually cares about, adds no value. An effective big data approach needs to ask the right questions, not just obtain answers.
Whilst science, technology and statistics can be leveraged to get answers; figuring out the right questions is an art. To capitalise on this art, you must hire people that are not only academic, but must also have business savvy. These people will understand your business and figure out questions in such a way that data can get them the answers. These people must also have an effective way of working together as a whole as well as within their various business teams.
Belief #3: Actionable insights are the goal
The goal should not be on obtaining just actionable insights. An effective big data approach should be able to take these insights and deliver the most impact.
Actionable insights are great, but mean nothing if you don’t take it a step further to leverage those insights and deliver meaningful impact. Meaningful impact specifically means moving a metric or changing a product, behaviour or process. For example, coming up with a way to increase sales by 5% (insight) and then actually increasing sales by 5% (impact). Be accountable for ensuring insights lead to impact to maximize the value of big data for your business.
The actual presentation (12 mins) follows below and is well worth viewing.
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