At DataScience, all analysts work on a single virtual machine called “data science tools.” This presentation discusses the path to building a singular virtualized machine used to scale across our current staff and to quickly onboard new staff.

1. Engineering a Platform
Scaling DataScience

2. Who is DataScience?
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● Do you need…
● …insights about your data?
● …to hire or train data scientists to provide
actionable insights?
● …a platform for consuming cutting-edge
data science and publishing within your org,
without having data scientists doing ops
work?
● …to focus your data scientists on your core
business, while we provide models for LTV,
pricing, retention and more?
● Visit www.datascience.com!

3. Two Primary Challenges
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● Rapid Team Growth
● Team member onboarding
requires a low-risk, standardized
toolchain. Time to first
contribution is measured in
hours, not days or weeks.
● Dynamic Tooling Landscape
● Best-of-breed data tools are
always changing. Our culture and
platform encourage
experimentation and evaluation
of new tools and techniques.

4. Rapid Onboarding
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● A packaged virtual
development environment
● No wrestling with complex
system dependencies and
version compatibilities
● A clean starting point to
quickly retreat at any time
● Monitoring and diagnostics
● Scripted automation for
customizing per user

5. Rapid Onboarding
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● Upgrades are vetted in
advance prior to wide release
● Continuous integration
provides automated feedback
● Group chat pushes
institutional knowledge out
into searchable, company-
wide record.
● A culture of sharing and
demonstration

6. Dynamic Landscape
● Configuration management to
quickly compose systems based
on requirements
● Software tools are constantly
evolving. A robust virtual
environment promotes
experimentation and iteration.
● Think in terms of categories of
tools not specific techs.
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7. Dynamic Landscape
● Version control: track changes
to analysis over time. promote
reproducibility
● Automated testing: An
engineering approach to analysis
quality
● Integrated publishing: A
publishing workflow that closely
follows the underlying analysis
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8. 8
Thank you.
Questions?
We’re hiring.

9. Appendix: Rapid Onboarding
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10. Appendix: Dynamic Landscape
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11. Thank you.