December 17, 2015• 3 minute read
Like the analysts who use Mode day-in and day-out to answer some of the hardest questions a business can throw at them, we hammer on our product for hours, every day. We're explorers, trying to make sense of data and telling stories once we do.
December 9, 2015• 6 minute read
Which database is best? The question, obviously, depends on what you want to use it for.
November 4, 2015• 6 minute read
Are our ebooks more successful on LinkedIn than on Twitter?
If you've ever worked with a marketer to understand campaign and channel effectiveness, I bet you've heard questions like these before. I know I've asked questions like these.
October 26, 2015• 4 minute read
There's an interesting discussion happening in the Silicon Valley data science community.
Last week about 100 data scientists gathered for the first ever WrangleConf, hosted by Cloudera. Good things start small.
October 16, 2015• 4 minute read
On Wednesday over 500 members of the data science community gathered at the Village in San Francisco for CrowdFlower’s Rich Data Summit.
It was great to see familiar faces, meet new people, and hear data scientists share perspectives. Despite a wide array of vantage points, the talks coalesced around some exciting ideas for the future of data science.
September 24, 2015• 3 minute read
Analyzing datasets that include email addresses can be a pain. But when armed with a few common operations, you can clean your data quickly and dive straight into the analysis. First, you should check if an email address is valid. And if it is, you can break an address into its component parts—before and after the “@” symbol—to classify users as consumers (e.g., gmail.com) or business users (e.g., microsoft.com).