businesses can go to outsource tasks and longer-term jobs to fully vetted people in their neighborhood. Our Mission: Empower people to do what they love. Our Vision: Revolutionize the world’s labor force.
data analysts • a handful of engineers who understand the schema(s) • 0 data science expertise In Jan 2014 • 1 full-time Data Scientist • every engineer familiar with major tables • a data subject-matter expert in every business area • no need for full-time analysts
analysts were spending the majority of their time creating reports for other teams ◦ ...and that others were spending a lot of time waiting for reports • Analysts are valuable, but at our stage we needed to focus on tools to enable product development. • This is only possible when you can empower everyone to become comfortable with data
learn our schema and help build out our key models within looker • (1 day) Looker on-site to train “power users” on LookML • (2 weeks) TR “power users” build out remaining looker models • (2 days) Looker on-site to train business users in reporting and exploration • (6 weeks) company becomes comfortable using Looker for day-to-day activities ◦ Beware the stages of acceptance
all team members having the ability to directly “play” with the data they care about, trends can be explored. Examples: • Moving tasks posted at the end of the month ◦ Change the distribution of marketing efforts to correlate and become more effective • Posters accept one of the first 10 bids ◦ Change the UI to direct rabbits to bid on tasks with less bids, leading to more tasks getting bids