What’s included

• Environment review: SQL/MI/Synapse, ADF, Databricks, Storage/Delta, Power BI.
• Performance audit: Query plans, ADF activities, Spark UI, data layout, scheduling.
• Cost analysis: Compute/storage right-sizing, retention, autoscale, cluster usage.
• Reliability & ops: Failures, schema drift, retries, alerts, runbooks, SLAs.
• Short report: quick wins, prioritised backlog, and estimated savings.

Process & timeline

1. Kickoff (Day 1): align goals, risks, access.
2. Diagnostics (Days 1–4): performance, cost, reliability checks.
3. Readout (Day 5–7): report walkthrough with recommended next steps.

What we need from you

• Read-only access to your environment (or screenshare if access is limited).
• One owner per area: data platform, BI, and FinOps (if available).
• Example workloads (slow reports, failing pipelines, costly jobs).

Deliverables

• PDF summary (findings, quick wins, backlog with effort/impact).
• Before/after metrics where fixes are made during the check.
• Roadmap options: optimise, migrate incrementally, or monitor.

FAQs

Will you make fixes during the health check?

Where safe and low-risk, yes—especially indexing, scheduling and configuration tweaks.

Do we need Databricks?

Only if the workload needs it. We’re happy SQL-first and add Spark where it genuinely helps.

Can you do this without production access?

Yes. We can run via screenshare and/or Dev/Test with representative workloads.