Big Data at Work is a good book for reviewing tested analytics case studies by Tom Davenport. As I began reading this I found myself reading an update to Tom Davenport‘s great analytics book Competing on Analytics that I read in 2008 which IMHO really set the standard. Big Data at Work is the follow up with tested business cases.
It seemed like an eternity that analytics are now realized as a critical business strategy for universities. Peter Drucker said it best: if you cannot measure it, you cannot manage it.
While much shorter than his Competing on Analytics, Big Data at Work is a must read. In Higher Education alone the Big Data at Work case studies by Davenport can serve as near perfect blueprints in the dynamic world of campus networks and services migrating to cloud.
Davenport needs to convince nobody that Big Data is a growing field, yet even in 2014 the number of colleges offering degrees in Big data science is not yet up to speed. More importantly he shares how traditional Business Intelligence is struggling to adjust to the analytics and big data era.
For as much as Big Data at Work contributes to the requirements in both technology and IT professionals, his suggestions that management stands in the way of more game changers outside of Silicon Valley. Yes Hadoop and MapReduce have forever empowered LInkedIn, Google, Yahoo and other startups. Healthcare, banking and insurance are markets who have already embraced and are excited about the abilities of big data for their customers.
Davenport is pretty upfront about what is needed: colleges have not fully embraced Big Data. Their mistake is assuming Big Data is a Computer Science degree. A good chapter of this book reflects on the inability of management to adopt Big Data for today’s competitive market. Is it surprising to see only a hand full of college programs sending grads to the likes of Google? More and more companies are looking to regional campus partnerships for Hadoop big data efforts. Yet many of those colleges still have no existing undergraduate or masters-level degrees in Big Data.