Data science is a collaborative effort

The other day our marketing guy dropped a laundry list of reports that he wanted me to produce. I work with him sometimes so I don't mind putting on a business intelligence hat occasionally to help him out. But I mustn't forget that driving long-term values to the business is what I am good at, so I had to say no to him. What's supposed to be a quick chat with him ended up in a hour long discussion to show case what I'm working on and demonstrating that I can do so much more than count things for him. In short, if you want data, ask the business analyst; if you want to solve problems, let's talk.

It's been said that Big Data analysis is a feedback loop. However, I don't think having the data science team toil away at data is the message. Who's to say that analytical steps in a big data reference model can't involve feedback from people in addition to models? For the past week, I've been showcasing a new internal data product to various stakeholders in our business. This one data product is now leading to a new process for our accountant, a product for our online marketing manager, and an innovative company-wide metric. All of this happened because we collaborated rather than delegated tasks. Analysing data is not a one-way process. Make it a feedback loop of math and people.