I'm not sure if I'm correct or not, but I see 2 types of big data guys. First there are the guys who know the tools - perhaps this is the "data engineer" referenced by rdouble. This guy would know all the tools, how to map data in and out of say something like Cassandra or HBase?
Then there are the guys who can properly analyze the data and turn that into something that can save an enterprise money. This is probably where the big bucks come in.
At my weekly codeandcoffee gathering we are discussing some problems we think can be solved by big data analysis. The actual underlying technology is merely an implementation detail, the value will come from the results. Our goal is to save a target enterprise 1% a year, and given our target customer is a $40 billion company, that is a lot of money we can charge. We're just discussing what ifs at this point.
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I'm not sure if I'm correct or not, but I see 2 types of big data guys. First there are the guys who know the tools - perhaps this is the "data engineer" referenced by rdouble. This guy would know all the tools, how to map data in and out of say something like Cassandra or HBase?
Then there are the guys who can properly analyze the data and turn that into something that can save an enterprise money. This is probably where the big bucks come in.
At my weekly codeandcoffee gathering we are discussing some problems we think can be solved by big data analysis. The actual underlying technology is merely an implementation detail, the value will come from the results. Our goal is to save a target enterprise 1% a year, and given our target customer is a $40 billion company, that is a lot of money we can charge. We're just discussing what ifs at this point.