Use Cases¶

Each demo takes one real-world data-engineering problem and shows how you can solve it end to end in a cost-efficient and scalable manner using Workspaces.

Here is the link to our YouTube playlist containing all the Use Cases videos: Altimate Workspaces — Use Cases.

For an introduction to workspaces and setup, see the Introduction page.

Demo 1 — Turn a Jira ticket into a Snowflake PR¶

Walk through how an Altimate Workspace turns a single Jira ticket into a reviewed Snowflake pull request — no context switching, no hand-holding. One prompt kicks off the whole flow: the agent reads the ticket, drafts the Snowflake code, runs it against a non-prod target, opens the PR, and closes the ticket.

Demo 2 — Migrate MS SQL procedures to dbt on Snowflake¶

See how a large batch of legacy MS SQL procedures gets migrated into dbt models on Snowflake under a medallion architecture. The workspace handles the trap-aware rewrites, deploys to an isolated schema for safety, and validates the results with a data-parity check so the migration is proven before it ships.

Demo 3 — Ship a dbt model change with tests and docs¶

See how a routine dbt model change — the kind that normally eats half a day — gets shipped end to end from a single prompt. The workspace updates the model, writes the required tests, refreshes the documentation, checks the downstream impact, and opens a reviewable pull request.

Demo 4 — Optimize a slow Snowflake query¶

A slow Snowflake query can cost a lot in credits and dashboard latency. This demo shows how the workspace analyses the query, rewrites it following best practices, proves the rewrite returns the same rows, and benchmarks the before/after on a non-prod warehouse — so the pull request lands with real evidence, not a guess.

Demo 5 — Fix a slow Databricks query from a Jira ticket¶

A slow Databricks SQL query can hold up a daily dashboard and burn warehouse time for every refresh. Starting from a Jira ticket, the workspace locates the query, reviews it against best-practice rules, rewrites it, and benchmarks the result on a dedicated warehouse before opening the pull request.