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What's Crucial- Big Data or Big Insights?
By Ujjyaini Mitra, Analytics & Data Science Leader & Mentor - Driving Data to Decision, Viacom18
Now their business development proposes to launch subscription scheme for premium customers, where if one pays certain amount they will be part of ‘premium club’, they get delivery charges waved off, plus buy one get one free on all food items from partner restaurants. They want to know what kind of subscription they should work on. This is business case. Based on the Big data analysis, they then suggest that one single subscription won’t work, given 50 percent people order corporate lunch, there must be a Weekday only custom subscription. Best to launch a Weekend only subscription pack also. This is Actionable insights from the analysis done.Without this point the big data or the big data analysis had no value to the business. Big data is challenge until you have right technology to store it and process it. It, however, can be tamed through new technology of cheap cloud storage, cloud computing, parallel processing in Spark cluster. Even after deploying the right big data infrastructure more than 40 percent organizations mention that they haven’t seen much value out of it. Why? • They have not received right insights driven from the data • Data-driven decision making has not been adopted at an enterprise level • No clarity what kind of questions could be answered through Big data • There have been more analysis-paralysis • Vision may be too short-term ROI gain • Data Science projects focuses to accuracy goal than adoption and ROI goal Analytics is not a magic wand. As soon as infrastructure is ready,many people believe, soon it will start churning deep insights. Unfortunately, it’s never that way. Most cases it takes minimum 18-24 months before Big Data team can start producing tangible insights. Can business wait so long? Unfortunately, in the VUCA digital world everything changing so fast, when analytics team completed a whole project the reason of project might have already gone by. So, it’s very important that business teams actively participate in prioritizing the Big Data exercises.