The trouble with media accounts of big data usage is that it tends to be cyclic: first hailing it and then bashing it mercilessly.
Make no mistake, Twitter is a big data company and it's looking to get even bigger. Hence yesterday's acquisition of Gnip, added to about four or so other similar acquisitions earlier. The end goal: Make Twitter a $100 million big data business.
There's a good post in The NY Times by Steve Lohr on the effects new technologies have on legacy companies like Teradata. It's well worth the read. "The challenge to old-line data...
Last week the American Farm Bureau Federation, a national independent farmers' group, met with John Deere, Monsanto and DuPont Pioneer to hammer out guidelines to protect farmer privacy and prevent potential market manipulations.
No one is happy about cloud providers getting to peep, parse and use your personal or business content. But, really, it's delusional to think any cloud provider can't paw through your data at will if and when it wants. So announcements like AlephCloud's lock on content to keep provider snooping away will likely be met with cheers--both from cloud users who seek privacy and security, and from cloud providers who want to prove their trustworthiness.
Intel is being very hush-hush on how big a dowry it paid to partner up with cash-hungry, over-achiever, Cloudera. This way Intel can focus on its core business while still fanning the big data flames that ignites server sales without getting lost in the smoke of building that fire. Hortonworks is probably crying at the wedding though.
So what do you need to know and consider when drafting a big data contract? Here's the laundry list…
Unlike many other technologies, retailers are adopting big data at a higher rate than their usual drag-feet adoption tendencies in the past. This is likely due to the fact that price pressures remain high and margins are increasingly pushed low. Indeed, if I'm surprised at anything in this report it is that big data's use in pricing was not pulled out specifically.
You shouldn't turn away from big data tools thinking your data isn't big enough or that you have no need for them. The truth is that many of today's big data analytics work well on most sized data sets. Plus your data will definitely grow over time so it's a good idea to have tools that scale with your incoming data pileup too.
Is there or will there be a bubble, i.e. a period where vendors will be made of gold and users will be paying top dollar? Will there be a get-rich-quick moment that will crest right before the bubble bursts?