This is a talk about how BI develops within a startup, from simple excel files to hard core data science. The talk proposes 4 main stages that BI teams go through as a company grows.
3. What is this talk about?
● Business Intelligence (BI) from a
product perspective - How does BI
build tech that people use?
● Organizational dynamics - How does BI
grow within a company and how does it
relate to other teams?
4. What is this talk based on?
● Using BI at Yahoo and Pollenizer
● Running BI at F&O
● Running BI at Flatbook
● BI porn addiction
12. Stage 1 - Analysis
● BI = Analysis
● Data availability not a major focus
● Key team member = someone who is
good at excel (generally founder, then
analyst)
● KPI = do analysis that helps business
14. Stage 2 - Dashboards
● BI = Data Availability + Visualizations
● BI now uses tech resources
● Key team member =
○ product oriented data engineer -or-
○ product oriented analyst w/ dev support
● KPI = dashboard usage
● Analysis can stay in BI or move to biz
units (product, marketing etc)
16. Stage 3 - Self Serve
● BI = Self Serve Tools + Data Warehouse
● High $$$ for tools and plumbing. . .
● But, this is the only model that scales
● Key team member = BI focused
engineers and product people
● KPI = tool usage + reduced analyst load
● Analysis should move to biz units
18. Stage 4 - Data Science
● BI = Data Science (Predictive Analytics)
● Some analysis is too hard for analysts, it
needs devs and math people
● Not for everyone, but high ROI for some
● Key team member = data scientists
● KPI = direct ROI to the business