by Angela Guess
Prakash Kini recently wrote in Tech2, “Every business worth its multi-million-dollar tagline wants to understand Big Data Analytics and leverage it. What I have realised is that it takes not only skill but finesse as well to understand and appreciate Big Data in all its beauty and derive true and timely business value from it. Of the many reasons that Big Data Initiatives could fail, I have picked out seven. Bear in mind that these are purely from my own experience in the field. For better context, I have put the reasons under three separate themes, organizational quagmire, old habits dying hard and new approaches creating new problems.”
Kini’s list begins, “(1) Queue of Unabated Requests. An investment bank elevated a lead technologist to Chief Data Officer. On taking up office, she was inundated with requests. Here’s a look at the top five requests: The CRO wanted to address regulatory and risk management gaps using Big Data solutions. The CMO wanted deeper customer understanding to inform marketing spends and drive revenue through personalization. The COO wanted to benchmark operations against competition and build dashboards to optimize and improve efficiencies. Trading Managers sought solutions around portfolio optimization, automated research and similar information. The CIO wanted to reduce costs by leveraging artificial intelligence for production monitoring and other technology operations.”
photo credit: Flickr/ amboo who?