How to Build a Dragon: Part 2! Models, mappings, and graphs.

This is the second in a short series of technical deep-dive presentations on Uber's Dragon data integration toolkit (https://eng.uber.com/dragon-schema-integration-at-uber-scale), which is written in Haskell. For an introduction to the formal data model behind Dragon, see the earlier presentation on Algebraic Property Graphs (https://www.meetup.com/Category-Theory/events/lcmnvrybclbgb). In contrast, these sessions are to be light on theory and heavy on implementation.

These events are scheduled week-to-week. In this session:

• A closer look at Dragon's core data model vis-a-vis Algebraic Property Graphs.
• Specification of language-specific data models in YAML.
• Schema-level and value-level mappings in Haskell.
• Data validation.
• Data and schemas as a graph.

Videos from previous session(s):

• How to Build a Dragon, Part 1: https://us02web.zoom.us/rec/share/5Jz3sldE4AbKsoTCRvE2AoQD4Hl6buEeHN30NI0U2DXDkthzIZ-GzxoFebkZF_3V.XfRRTg-3mpBqzh (passcode: X0TQ5dm=)

Other links:

• Release Dragon! (survey form) -- http://bit.ly/release_dragon
• Dragon: Schema Integration at Uber Scale (Uber Eng Blog) -- https://eng.uber.com/dragon-schema-integration-at-uber-scale
• Algebraic Property Graphs (paper) -- https://arxiv.org/abs/1909.04881
• Databook (Uber Eng Blog) -- https://eng.uber.com/databook
• TinkerPop 2020 (presentation/video) -- https://www.youtube.com/watch?v=CrFz64aF5sY
• A Graph is a Graph is a Graph (presentation/video) -- https://www.youtube.com/watch?v=aT1rF5qNjmU