Here are some points to ponder when hiring data professionals:
1. look for candidates with a strong educational background in analytics/statistics. you want someone who knows more than you do about handling copious amounts of data.
2. the ideal candidates will have specific experience in your industry or a related industry. "when you have all those ph. d.s in a room, magic doesn’t necessarily happen because they may not have the business capability," said andy rusnak, a senior executive at ernst & young.
3. search for potential candidates from industry leader organizations that are more advanced in big data.
4. communication skills are a must. look for a candidate "who can translate ph. d. to english," says sap chief data scientist david ginsberg. he adds, "those are the hardest people to find."
5. find candidates with a proven record of finding useful information from a mess of data, including data from questionable sources. you want someone who is analytical and discerning.
6. look for people who can think in 8- to 10-week periods, not just long term. most data projects have a short-term focus.
7. test candidates’ expertise on real problems. netflix's director of algorithms asks candidates, "you have this data that comes from our users. how can you use it to solve this particular problem? "

questions:
1. let’s say you work in a metropolitan city for a large department store chain and your manager puts you in charge of a team to nd out whether keeping the store open an hour longer each day would increase profits. what data might be
available to your decision-making process? what data would be important to your decision?
2. what kinds of data might we want in ob applications?
3. as braver man notes, one problem with big data is making sense of the information. how might a better understanding of psychology you sift through all this data?