Databricks Community Meetup Chicago

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About us

With origins in academia and the open source community, Databricks was founded in 2013 by the original creators of Apache Spark™, Delta Lake and MLflow. As the world’s first and only lakehouse platform in the cloud, Databricks combines the best of data warehouses and data lakes to offer an open and unified platform for data and AI.

Databricks is the lakehouse company
Today, more than 7,000 organizations worldwide — including ABN AMRO, Condé Nast, Regeneron and Shell — rely on Databricks to enable massive-scale data engineering, collaborative data science, full-lifecycle machine learning and business analytics.

Headquartered in San Francisco, with offices around the world and hundreds of global partners, including Microsoft, Amazon, Tableau, Informatica, Capgemini and Booz Allen Hamilton, Databricks is on a mission to simplify and democratize data and AI, helping data teams solve the world’s toughest problems.

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Databricks Oct Meetup
Tue, Oct 20 · 5:30 PM CDT
200 E Randolph St, 200 E Randolph St, Chicago, IL 60601, USA, Chicago, IL, US
Speakers
Thoughtworks: Eric Nagler and Arun Srinivasan
Databricks: Kevin Hartman

Location
200 E Randolph St. Chicago Floor 25

Hosts
Thoughtworks

Agenda:

5:00-5:30p.m Happy Hour
5:30 (45–60 min) — AI-Ready Semantic Layers: from ontology to Genie
- The problem: metric views give agents dimensions & formulas, not part-of / is-a / rolls-up-to — and Genie Ontology only infers what your assets already encode (the "right answer, wrong rollup" failure — not a model problem).
- The moat: the platform moved the floor; the domain-specific semantic layer (metric views, glossaries, ontology) is still the differentiator.
- The build: rapid discovery with the Ontology Accelerator → where to model non-metric concepts (tables vs. UC semantics vs. ontology vs. agent) → two live demos (infer vs. supply; end-to-end Genie Agent).

6:30 (~60 min) — Consort (open source)
- What it is: keeps AI-written code clean and correct — a deterministic state machine drives /plan → /design → /build → /deploy so agents can't skip steps, weaken tests, or drift from spec.
- Why Lakebase: every git branch auto-pairs with a copy-on-write Postgres branch in ~1s — tests run against real data, not mocks, and schema evolves in lockstep with code.
- How it works: 8 role agents (Spec Author, Architect, DBA, Test Strategist, UX, Navigator, Driver, Product Owner) communicate only through immutable artifacts; RED → GREEN → refactor; human-approval gates that fail closed.
- The differentiator: engineering discipline enforced by contract, not suggestions — "green" means a real test pass on live infra. Live /consort:start scaffolds repo + paired DB + agents (StockFlow sample).
24 attendees