The scenario Jill Dyche, vice president of SAS Best Practices, describes in a recent article for Information Management is representative of the way many companies are approaching big data. At a recent conference about analytics strategy, Dyche was approached by a woman and asked to explain all she knew about big data.
Dyche asked the woman why she wanted this information and describes the response she received as follows: "'So we can start watching social media comments,' she says, as if she's explaining why I should tie my shoelaces and get a good night's sleep."
This phenomenon has to do with the amount of buzz that's been generated around big data, and sometimes the hype is so big that adopters lose sight of their exact goals.
In a recent post for Kalido Conversations, Mike Wheeler explains that firms can get caught up in their pursuit of fast, cheap, yet large-scale solutions and lose sight of quality. Data quality is actually essential to their successful use of the content for decision-making.
Wheeler suggests that if users don't trust their data enough to take action on its own and formulate decisions automatically, they may need to employ better cleansing strategies and governance.