The Real Life of a Data Scientist
How’s this for a definition of Big Data: If it doesn’t make sense in a system built 10-plus years ago using principles from 30 years ago — then you’re dealing with Big Data.
That’s the unusual definition offered by William McKnight in a recent Q&A published on, oddly enough, the Huffington Post. Phil Simon, who consults, writes and speaks about technology, data and business issues, conducted the interview.
McKnight makes the case for why data outranks even the storefront as a strategic asset today.
“What used to be optional and prioritized well after the operational aspects of storefront, supply chain and transacting business is what now sets companies apart,” McKnight told Simon. “If you look at the leaders in industry, they are masters of the information asset. They save more information, make it more accessible to a broad internal community and have developed business leaders that are able to consume the data and advance the business with it.”
So what’s the big key to using data? Rather than arguing for particular technology categories — MDM, Hadoop, streaming data, NoSQL — McKnight says they’re all important, but what matters most isn’t the particular solution.
Instead, he argues, “The key is to get the right workload — a combination of the data and its processing — into the right platform based on its unique characteristics.”
Workload and scalability always come up as key parts of any modern architecture, but I’m 95 percent sure this is the first time I’ve heard workload listed as the key element.
It makes sense, though, and he drives home the point with an example most of us can relate to: The typical SAP upgrade. It’s running, it’s working — but it never quite performs as promised. It gets better, but even as it improves, expectations grow — so it never manages to close the gap between expectations and actual performance.
You don’t see a whole lot of information management discussions that really take two steps back and view the big picture. The problem they tend to run into is that they’re so general as to say nothing.
This Q&A actually offers some specific takeaways:
- Agile information management works best when it’s surrounded by an agile organization.
- Organizations need options — lots of them. Don’t limit yourself to on-premise, or the cloud, or MDM or Big Data. Look at how all these tools can be used.
- MDM and data virtualization should be considered, whatever platform you choose.
If you’d like to read more, McKnight’s newest book is Information Management: Strategies for Gaining a Competitive Advantage with Data (The Savvy Manager’s Guides).
