4 — Module Rhythm
Facilitator Guide — repeat every module
Day-of navigation (follow in order on delivery day):
Index → 2 Room prep → 3 Schedule & roles → 4 Module rhythm → 5 Module 7 runbook → 6 Classroom fixes → 7 Close & after
Before class: Platform dependency order (sidebar · links into checklist)
On this page
- Per-module checklist
- Module-specific notes
- Per-module UI checkpoints
- Optional modules (8–9)
- Next step
Per-module checklist (repeat every module)
Every main-day module follows the same five-step rhythm — see module delivery pattern for timing details.
Module-specific notes
In main-day agenda order:
| Module | Trainer note |
|---|---|
| Story | Capture design whiteboard — revisit at 16:30 |
| 1 Fundamentals | Elena whiteboards medallion; Priya lists KPIs — keep to 35 min |
| 2 Databricks | Sofia voice: prototype before SQL simplification |
| 3 Snowflake | “Same architecture. Different implementation philosophy.” |
| 4 dbt | Elena: dbt on Snowflake |
| 5 Production | LSDP naming; what runs every night without you? |
| 6 AI | Cortex LLM only — do not demo ML.FORECAST |
| 7 Wrap-up | Theory ≤5 min · open discussion guide |
Per-module UI checkpoints (co-trainer verifies before each module)
| Module | Attendee UI should show | Co-trainer check |
|---|---|---|
| 2 Databricks | Cluster Running (green dot) in Compute page; notebooks visible in Workspace | Confirm all attendee clusters started; trainer Git folder MHP-DE-Workshop-2026 shared Can Run to trainees |
| 3 Snowflake | Snowsight open on attendee’s own trial account; 02_account_setup.sql completed; warehouse Started |
Walk around — confirm each attendee has DE_MASTERCLASS database and DE_WORKSHOP_ROLE created; ADLS2 SAS token distributed and working; remind attendees to run 05_cortex_access.sql on their trial (you have no access to grant Cortex roles for them) |
| 4 dbt | Terminal open in Codespaces; Exercise: dbt § Configure .env done; dbt debug --target snowflake passing |
Walk around — check terminals for green All checks passed!; if failing, confirm .env has Snowflake trial + assigned ATTENDEE_ID |
| 5 Production | Jobs & Pipelines page accessible in Databricks (formerly Workflows → Delta Live Tables; renamed to Lakeflow Declarative Pipelines); Workspaces SQL files with Task SQL ready | Pre-create one Lakeflow pipeline as demo; verify TASK_HISTORY() returns data |
| 6 AI Features | Genie icon visible in Databricks sidebar (under SQL section); Workspaces SQL files ready for Cortex SQL | Confirm AI_COMPLETE returns results; if access denied, attendee re-runs 05_cortex_access.sql as ACCOUNTADMIN on their trial |
| 7 Wrap-up | No portal needed — whiteboard and discussion only | Print architecture decision matrix handouts |
Optional modules (8–9)
Deliver Module 8 before Module 9 when running both optional sessions — Marcus needs live dispatch before tip-prediction ML in the story arc.
| Module | Attendee UI should show | Co-trainer check |
|---|---|---|
| 8 Streaming | Databricks cluster with Kafka Maven libs installed; Snowflake warehouse running | Verify Kafka libs on cluster (Compute → Libraries tab); Aiven topic has events flowing |
| 9 ML | Databricks AI/ML → Experiments page accessible; Workspaces SQL files ready for ML.FORECAST |
Confirm each attendee ran 05_cortex_access.sql on their trial (SNOWFLAKE.CORTEX_USER); ML Runtime cluster available |
Module 8 trainer line: “YellowLine NYC would stream taxi GPS. We use Aiven user-activity so every attendee gets a live Kafka topic.”
Module 9 trainer line: “This is not Module 6 again — we’re training models, not asking an LLM to write SQL.”