Big Data and Its Less-Than-Gentle Lessons
August 1, 2013
I read “9 Big Data Lessons Learned.” The write up is interesting because it explores the buzzword that every azure chip consultant has used in their marketing pitches over the last year. Some true believers have the words Big Data tattooed on their arms like those mixed martial arts fighters sporting the names of casinos. Very attractive I say.
Because “big data” has sucked up search, content processing, and analytics, the term is usually not defined. The “problems” of Big Data are ignored. Since not much works when it comes to search and content processing, use of another undefined term is not particularly surprising. What caught my attention is that Datamation reports about some “lessons” its real journalists have tracked down and verified.
Please, read the entire original write up to get the full nine lessons. I want to highlight three of them:
First, Datamation points out that getting data from Point A to Point B can be tricky. I think that once the data has arrived at Point B, the next task is to get the data into a “Big Data” system. Datamation does not provide any cost information in its statement “Don’t underestimate the data integration challenges.” I would point out that the migration task can be expensive. Real expensive.
Second, Datamation sates, “Big Data success requires scale and speed.” I agree that scale and speed are important. Once again, Datamation does not bring these generalizations down to an accounting person’s desktop. Scale and speed cost money. Often a lot of money. In the analysis I did of “real time” a year or two ago, chopping latency down to a millisecond or two exponentiates the cost of scale and speed. Bandwidth and low latency storage are not sporting WalMart price tags.
Third, Datamation warns (maybe threatens) those with children in school and mortgages with, “If you’re not in the Big Data pool now, the lifespan of your career is shrinking by the day.” A couple of years ago this sentence would have said, “If you’re not in the social media pool now, the lifespan of your career is shrinking by the day.” How long with these all-too-frequent “next big things” sweep through information technology. I just learned that “CIO” means chief innovation officer. I also learned that the future of computing rests with synthetic biology.
The Big Data revolution is here. The problem is that the tools, the expertise, and the computational environment are inadequate for most Big Data problems. Companies with the resources like Google and Microsoft are trimming the data in order to get a handle on what today’s algorithms assert is important. Is it reasonable to think that most organizations can tackle Big Data when large organizations struggle to locate attachments in intra-organization email?
Reality has not hampered efforts to surf on the next big thing. Some waves are more challenging than others, however. I do like the fear angle. Nice touch at a time when senior managers are struggling to keep revenues and profits from drifting down. The hope is that Big Data will shore up products and services which are difficult to sell.
Catch the wave I suppose.
Stephen E Arnold, August 1, 2013
Sponsored by Xenky
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