by Angela Guess
David Linthicum of InfoWorld recently wrote, “Big data is good. The cloud is good. Now, how do we actually make the whole thing work? The truth is not many best practices have emerged on how to move to big data. We have the migration to data warehousing and business intelligence as an existing model, but as I look at what big data really is, it’s clear that big data adoption is a different type of problem. Much of that experience in data warehousing and BI isn’t relevant, and it may even lead to some dead ends.”
He goes on, ” For now, the proper path is more through trial and error than following proven concepts. The answer to how to best do big data is the classic consultant’s response: It depends on what you’re trying to do. The bottom line is that you have to experiment. But you need not do so blindly. The emerging role of data scientist can help direct those experiments within an appropriate framework, in the manner of research scientists in any field. Data scientists can get you the answers to big data, as long as you understand that a scientist must run a lot of experiments. At this point, experimentation is the best practice in moving to big data. Get a data scientist or two to design and run these trials.”
