Big Data Fans: The Nitty Gritty
Love talking about Big Data? I recommend doing a bit of reading. I found “What I Learned from 2 Years of Data Sciencing” refreshing. Quotes I noted were:
- With reference to Big Data projects where the author worked: “None of these projects gained traction within the company and became abandoned.”
- With reference to the work required: “Much of the efforts spent for those projects were in getting the right data into the right shape.”
- “Little did I know that we’ll be cleaning and shaping data for most of my second year at uSwitch.”
- “In practice, I was just cleaning and shaping data.”
- “Figuring out the right work to do is one of the most difficult tasks for a data science team. It doesn’t help with the fact that the data science role is so vague.”
- “Figuring out where to devote our time and effort is not as easy as it sounds.”
- “Unless someone or something can act on the data, results can only satisfy intellectual curiosity. A business can’t survive on funding people to carry out academic studies forever.”
- “If cleaning vast amount of data, being clueless as to what to do, and debating with colleagues sound like a challenge that you want to take on, I know a company in London that’s looking for a data scientist!”
Is there a message about the nuts and bolts of data? Is analytics repeating the sins of the first enterprise search vendors? It is so much easier to sell sizzle than focus on the basics like figuring out what’s important and getting valid data. Let’s just take the easy path seems to be one risk for analytics cheerleaders.
Stephen E Arnold, December 22, 2013
Phi Beta Iota: Big Data is an extension of the American penchant to substitute technology for thinking — expensive technology generally bought without a functional requirements analysis, without a cost-benefit analysis, without a holistic analytic framework, and without any clue as to what end state this “big data” might support. Big Data is Big Garbage.
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