Biggest Hadoop mistakes and how to avoid them

Hadoop, for all its strengths, is not without its difficulties. Business needs specialized skills, data integration, and budget all need to factor into planning and implementation. Even when this happens, a large percentage of Hadoop implementations fail. To help others avoid common mistakes with Hadoop, I asked our consulting services and enterprise support teams to share their experiences working with organizations to develop, design and implement complex big data, business analytics or embedded analytics initiatives. These are their top seven mistakes, and some advice on how to avoid them. Mistake 1: Migrate everything before devising a plan As tempting as it… [Continue Reading]