There's not much of a market for raw data. But if you have output from sophisticated, trustworthy predictive models for sale, then you stand to make some sizable money. The problem data brokers have now is in branding their big data so buyers can know the difference--and the value.
While the business world has recently experienced a rapid growth in data and discovered ways to manage and use it, the new tools have yet to fully measure up to handling the mega-data scientists are still trying to get a handle on.
Check out this infographic for tips on explaining big data to people who work anywhere and with anything other than big data.
Beyond rendering some really great personal experience and action videos, this accomplishment can lead to a much needed means to examine, compare and analyze video data from nearly any camera source, including those in extreme environments.
Former CIA pros use their spy experience with big data to sort out huge investment portfolios and predict their crash.
According to a recent Oxford Economics study, only 31% of the companies surveyed have a data and application migration plan.
At its heart Ancestry.com is a big data driven company and is about using big data to tell personalized stories--and to create them, as well. I chatted with Bill Yetman, vice president of engineering at Ancestry.com, to learn how they do what they do.
Bernard Marr has a good post in SmartDataCollective on the four key layers of the big data system.
Among the list of more challenging data to analyze, human brain data certainly ranks high. Thunder is a library of tools built on the Apache Spark platform specifically for use in analyzing large neural data sets.
The Consular Consolidated Database, or CCD, at the U.S. State Department has crashed. Significant problems have been occurring since July 19 and, as of this writing, there's no word on when the system will be back up again.