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Project Meeting 2022 April

samanthashain edited this page Apr 6, 2022 · 4 revisions

Meeting Goal

Convene Data Gen contributors to discuss community contributions, upcoming events, and project leadership.

Date Time

April 6, 3 PM ET AMER

Present

Patrick M, Samantha S (recording), Junette T, Jennifer C, Eileen K, Cori O, Jess L, Jung M, Aaron C, Emily H, Paul P

Snowfakery Training Debrief (Junette)

  • The deck is very well prepared, very well designed for beginners
  • Junette is an excellent presenter. Clear, thoughtful, precise
  • Encouraging tone
  • Useful "roadmap" (now we've done this, next we're going to do this)
  • Timing was excellent
  • Attendance was 177, with 165+ staying for the full event
  • Cori's VP and Sam's friends said the training was excellent
  • FAQ: What does Snowfakery not do? Data masking
  • 50% partners, 40% customers, 10% staff
  • 98% customer satisfaction
  • cci task run snowfakery is faster for large batches. could load 10,000 to show the capability. Paul's bias is scale as a performance engineer.
  • there are slightly different considerations for snowfakery commands vs cci commands
  • new idea - cci command with a dry run option
  • feedback - when the slides have links, try to post in the chat
  • first time doing a webinar

Snowfakery updates (Paul)

  • Snowfakery 3.0 introduced ability to update records
  • upsert functionality is coming soon (safe harbor)
  • Snowfakery now handles decimals better (ie longitude and latitude) - talk to Paul if you need to learn more about this
  • random references to nicknames (FAQ!!!)
  • in the past, you can traverse object relationships unless you are using random reference. Soon this will work for random references too (safe harbor)

Next Full Community Sprint! May 4-5

we need to be able to set some general parameters for what we hope to achieve

  • what are our major workstreams? (1) snowfakery recipes (2) faker providers (3) Fake ETL tool reviews
  • what is the categorization framework for recipes (1) getting started: no macros, no include, no providers (2) scenario driven recipe: useful for product demos, unlikely to be reproduced (3) component recipes: more complicated features, designed for modular reproducibility
  • attendees
  • breakout groups (7)
  • marketing
  • prep intro slides: Eileen
  • prep issues: Recipe workstream (Jennifer C)
  • vols for beginner Snowfakery room
  • action item: move tool comparison into issues

collecting emails from project participants?

Snowfakery working session

  • 4/14 1:30-3:30 PM ET AMER
  • BYO project or claim an issue
  • BYO buddy
  • Limited support available (synchronous)

bike rack

  • video demos of Snowfakery
  • panel on DEI and fake data
  • recipe organization structure
  • recipe reviewer capacity building
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