Michael Erasmus
A collection of 5 posts
This post is co-written by David Gasquez . All the way back in late 2014, we wrote short little blog post about our first big redesign of our data architecture at Buffer. Back then, the data team consisted of 2 people, handling everything from data infrastructure to analysis and business intelligence (with some part time help from our CTO) within a company of just 25 people. We built out the initial
A while back I read a pretty inspiring blog post, Serving Analytics the Right Way It’s a great read by Kevin Teh, a Data Scientist at OpenDoor. Like at Buffer, they also use Looker as an analytics platform. One part of the post I really liked was the idea of ‘Bringing data to the Team’. “all of the data is updated in real time without requiring an analyst to do any repetitive manual work. However, t
This post is co-written by Julian. At Buffer, we’re trying hard to be mindful of diversity within our team, as well as doing as much as we can to improve diversity of people in our industry. In an effort to understand diversity across our team as well as people who apply to work at Buffer, we started started collecting diversity data via questions in an anonymous survey. Once we had some data trickling in, we starting graphing some of the data and eventually decided to write a dashboard to sha
At the start of 2014, I decided I need to make some changes in my life. I was working in an office in one of the coolest startups in Cape Town. I had worked in an office pretty much all of my career. I was also commuting to work and back, taking about an hour and a half of my day. Commuting has always been part of work for me too. I have a beautiful family; my wife who works from home and away on weekends shooting as a wedding photographer, my four-year-old son and my baby daughter, who had ju
Up until recently at Buffer, we had a big problem: we were drowning in data. Buffer is a data-driven company. So many of the decisions we make hinge on data that we collect and analyze. We track and measure analytics data for all kinds of things – user behavior, how our A/B experiments are running, as well as system-generated data such as API logs. As outlined in this post by Sunil, we have built a pretty robust platform for tracking and measuring data, all powered by Amazon’s SQS and MongoDB.