The key to data science? Telling stories
We weren't at last week's LeWeb conference in Paris, France -- dommage! -- but D.J. Patil, data scientist-in-residence at the venture capital firm Greylock Partners, was, and he had a few choice words to offer the crowd about data science.
Patil says data scientists are a lot like journalists in that both collect data to tell stories. It's that story part that's most important -- a successful data scientist is one who can weave a cohesive narrative from the numbers and statistics.
Like journalism, there are many stories to tell from the same set of data, and data scientists must choose carefully. And just like you, the reader, are wondering what the point of this article is -- what's my key takeaway? -- there's a level of subjectivity that data science doesn't normally get credit for.
The Wall Street Journal's Ben Rooney was there to capture Patil's words.
Five highlights:
- "Data science is about creating narratives. It is about creating analogies, about using complex data to tell stories."
- "Data science is about trying to create a process that allows you to create new ways of thinking about problems that are novel, or you are trying to use data to create or make something."
- "We need to separate out the idea of 'big data,' from being 'data driven.' Companies need to be data-driven but often you don't need lots of data to do something."
- "Subjective areas are where data science shines. It allows us to ask questions...the point is to have a debate."
- "We posted job postings for the same job but with different titles. Data scientist, research analyst, research scientist -- the people that were the true creative curious types all came through the data science job title."
The full talk, in a video, below: