Case Study
Operationalising Workforce Data in Databricks
Industries
Mining
key Services
additional services
Data Engineering
Databricks
A major Australian mining company needed a reliable Databricks Lakehouse foundation for daily workforce reporting at enterprise scale. Mivada delivered automated pipelines in three months, reducing manual validation from 12–15 hours per week to ~0.5 hours, and achieving >98% SLA compliance for daily data availability.
The Challenge
The client had recently adopted Workday as the core HR system and uses a Databricks Lakehouse to support reporting, analytics, and operational decision-making across workforce planning, compliance, and payroll accuracy.
But the reality on the ground was inconsistent. Key HR datasets didn’t arrive reliably in Databricks each day, which meant teams fell back on manual extracts and repeated checks to make reports usable. That created delays, uncertainty in the numbers, and growing audit risk—especially as expectations for Workday-based reporting increased.
There was also a transition challenge: historical reporting had been built on SAP-aligned structures, and the client didn’t yet have a standardised ingestion pattern or data model for Workday—yet the business still needed daily, dependable outputs.
The Mivada Approach
Mivada treated this as a reliability and governance problem first, and a technology build second. The goal was simple: make sure workforce data could move from Workday into the Databricks Lakehouse every day, on time, with confidence in the numbers.
We began by validating what was already available through existing Workday extracts (RaaS/API) and identifying the gaps that were driving manual rework—missing fields, unclear transformation rules, and data quality checks that weren’t consistently applied. From there, we established a repeatable Lakehouse pattern in Databricks using Delta tables and clear data layers (bronze → silver → curated), so each step of the process was traceable, testable, and easier to support.
Because workforce data changes over time, we designed the model to preserve history, not overwrite it. Using SCD2 logic, the Lakehouse could maintain effective-dated changes cleanly—supporting auditability and more accurate reporting.
Finally, we operationalised the solution: scheduling daily runs, adding monitoring and alerts, and putting the right validation checkpoints in place so the team could focus on exceptions instead of performing the same manual checks every day.
The Outcome
Reliable daily data availability
Workforce datasets now arrive in the Databricks Lakehouse on a consistent daily cadence, completing within the agreed window and meeting the availability SLA more than 98% of the time in Phase 1.
Manual effort reduced to exception review
Time spent on validation and ad hoc checks dropped from ~12–15 hours per week to ~0.5 hours per week. The team shifted from repeated manual reconciliation to lightweight exception handling when something genuinely needs attention.
A scalable Lakehouse foundation for future phases
The client now has a repeatable, scalable framework for onboarding additional workforce datasets—anchored in the bronze/silver/curated pattern, Delta tables, and history-preserving SCD2 structures—ready to extend beyond Phase 1 as new objects and reporting needs are prioritised.
The Long-term Impact
The organisation now has an operationalised Databricks Lakehouse foundation for workforce data that is repeatable, auditable, and scalable. It reduced day-to-day operational risk immediately, improved trust in reporting, and established reusable patterns and controls that make future Workday-to-Lakehouse expansions faster, safer, and more consistent.
*Client details have been generalised to respect confidentiality.
Related Case Studies
Continue Reading
Move Forward with Genuine Understanding
Partner with Mivada and harness the power of collaboration, because when you bring technology and the right people together, there’s no limit to what you can achieve.
Subscribe to stay in the know
Enter your business email to receive updates from Mivada. Please refer to our privacy policy for details or to contact us. You can unsubscribe at any time.
Mivada acknowledges the Traditional Owners of Country throughout Australia and acknowledges their continuing connection to land, waters and community. We pay our respects to the people, the cultures and the Elders past, present and emerging.
© 2026 Mivada Pty Ltd
