4 — Module Rhythm

Facilitator Guide — repeat every module

TRAINER ONLY

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 (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; 00_account_setup.sql completed; warehouse Started Walk around — confirm each attendee has DE_MASTERCLASS database and DE_WORKSHOP_ROLE created; SAS token distributed and working
4 dbt Terminal open in Codespaces or Docker with dbt_project/ directory; dbt debug --target snowflake passing Walk around — check terminals for green All checks passed!; confirm profiles.yml uses DE_WORKSHOP_ROLE and DE_MASTERCLASS
5 Production Jobs & Pipelines page accessible in Databricks (formerly Workflows → Delta Live Tables; renamed to Lakeflow Declarative Pipelines); Snowflake worksheets 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); Snowflake worksheets ready for Cortex SQL Confirm AI_COMPLETE returns results (run test query); Genie page loads
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 — story and editorial convention; see module prerequisites.

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; Snowflake worksheets ready for ML.FORECAST Confirm USE AI FUNCTIONS privilege + CORTEX_USER role granted; 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.”

Next 5 — Module 7 runbook 30-minute capstone block at 16:30