Data & AI
Databricks Consulting for Governed Data and AI at Scale
Mivada is an Australian-owned Databricks Partner, helping organisations move beyond siloed reporting to a governed Lakehouse designed to scale AI and ML across the business. Our consultants bring deep experience in regulated, compliance-heavy industries, connecting siloed data into one trusted foundation for every decision. From pipeline modernisation to Lakehouse architecture, we build the governance and platform foundations that turn your data into decisions your business can act on.
Our Clients
Technology Partners
Mivada + Databricks™
Mivada is an Australian owned Databricks Partner, that helps organisations run connected data platforms. We unify data engineering, analytics, and AI on the Databricks Data Intelligence Platform. Our certified consultants design Lakehouse architectures, implement Delta Lake pipelines (batch and streaming), and integrate Databricks with Workday, Payroll, Finance, and RPA to deliver governed KPI stores and real-time insights.
Databricks Services at Mivada
What we do
Our goal is to help you clarify your scope, sequence the work effectively, and gain measurable outcomes. We can support your business case development, define your roadmap, review migration risks, design integration architecture, and build your governance model.
How we do it
This creates a clear, sequenced roadmap so investment lands where it matters most and governance strengthens as you scale.
What we do
We modernise and migrate your legacy data platform to Databricks Lakehouse, engineered to scale and optimised for performance.
This starts with designing the target architecture and migrating off legacy warehouses and on-premise estates, with Unity Catalog, workspaces and clusters configured correctly from day one. We then build the CI/CD and DevOps foundations so pipelines stay maintainable as they grow. Our focus is architecture that holds under growth, not one that needs re-platforming in eighteen months.
How we do it
The result is unified, trusted data on a platform that performs reliably and scales without rework.
What we do
Pipeline and model workload engineering on Databricks, built to run in production, not just to demo.
This covers Lakeflow and DLT pipeline development for batch and streaming ingestion, through to feature engineering and ML model deployment. Once models are live, we keep them there: MLOps, model lifecycle management, and ongoing cost and performance tuning so workloads stay efficient as they scale.
How we do it
The result is pipelines and models that hold up under real production load and change.
What we do
We deliver single-source-of-truth reporting and self-service analytics and business intelligence on Databricks that you have confidence in and trust.
This covers Genie and AI/BI implementation, dashboard and reporting builds, and the semantic layer and metric definitions that sit underneath them. For businesses that need it, we extend into self-service enablement, embedded analytics, digital analytics and customer segmentation. The focus is decisions the business can act on, not dashboards nobody opens.
How we do it
This means stakeholders get clear, consistent insights on the metrics that matter, reducing errors and time spent wrangling data.
What we do
As AI scales across your business, so should the governance and trust controls that keep it accountable.
We start with the foundations: Unity Catalog governance design, data lineage and quality frameworks, and access and permissions modelling. From there, we extend into model risk and compliance controls, Unity AI Gateway implementation, and audit and monitoring frameworks. The focus is trust that scales with usage, built into the platform rather than written once and left behind.
How we do it
This means governance and trust controls that keep pace with how the business actually uses data and AI.
What we do
We connect Workday, including Workday Data Cloud, into your Databricks Lakehouse, so workforce data sits alongside payroll, finance and the rest of the business instead of staying locked in its own silo.
This starts with mapping Workday and Workday Data Cloud models against your Lakehouse architecture, then building the ingestion pipelines that bring HCM, payroll and finance data in reliably. We bring over a decade of hands-on Workday and payroll delivery to that mapping work, award interpretation, superannuation compliance, multi-state rules, so the integration accounts for where workforce data actually goes wrong before it lands in the platform. Our focus is a workforce data feed you can trust, not a generic connector.
How we do it
This means workforce data that’s accurate and governed from the point it enters the Lakehouse, not cleaned up after the fact.
What we do
Ongoing platform operation once the delivery team leaves, so the outcome doesn’t decay after go-live. We provide Adaptive AMS, a flexible blend of support, maintenance and enhancement for data platforms and analytics products.
This covers the day-to-day: platform monitoring and incident response, cost and performance optimisation, and release and change management. Alongside that, we handle user support and enablement, capacity planning and continuous improvement roadmaps, keeping the platform current as needs change. The focus is a platform that stays governed, performant and adopted long after the project closes.
How we do it
This keeps platforms stable, secure, and continuously improving — without heavy lift each time you need change.
Why Mivada for Databricks™?
Mivada is a 100% Australian owned firm that helps organisations run connected data platforms. We design Databricks environments that integrate, automate, and operate in business as usual.
Australian Leadership, Global Reach
Headquartered in Sydney with offshore capability
Deep Local Compliance Knowledge
Especially in Australian payroll, superannuation, and EA compliance
Trusted Partnerships
Long-term relationships with clients like Qantas, Macquarie University, and Guzman y Gomez
Human-Centred Consulting
Our consultants are valued, not treated as numbers — and that’s reflected in the quality of work our clients experience
Frequently Asked Questions
Yes. We’re an Australian-owned Databricks Partner, delivering data, analytics and AI engagements from early adoption through to scaled, production-ready use cases. Our strength is lakehouse architecture and data engineering, backed by a decade of experience keeping mission-critical systems accurate and compliant.
Yes. Typical scope includes platform support, performance and cost optimisation, incident and problem management, minor enhancements, release support, and service reporting across Databricks and related data integrations.
We report against delivery milestones, service performance, incident resolution and improvement activity, set against the operational targets we agree with you upfront.
Yes. We tailor the delivery model for your engagement, but Australian leadership and customer-facing roles stay onshore in every case. Offshore capacity, where used, is aligned to Australian business hours so you get scale and cost efficiency without losing accountability.
Most partners hand over a platform at go-live and move to the next project. We stay accountable for how it runs afterwards, because that’s where governance, cost, and adoption problems usually show up.
That standard comes from where we started. Mivada has spent twelve years running mission-critical HR and finance systems for enterprise clients, environments where a broken workflow means someone doesn’t get paid correctly or a board doesn’t get accurate numbers. We bring the same operating discipline to Databricks.
Yes. We provide Databricks consulting across advisory, architecture and governance design, led onshore by senior Australian consultants. As a 100% Australian-owned Databricks Partner, engagements stay accountable to local teams, backed by a decade of experience in regulated, compliance-heavy industries.
Our implementation approach covers target-state architecture, Unity Catalog and workspace setup, and migration off legacy warehouses, followed by the CI/CD foundations that keep pipelines maintainable as they grow. We’re a newer Databricks Partner, so we pair that approach with over a decade implementing mission-critical Workday, payroll and finance systems, the same operating discipline applied to a new platform.
Yes. Workday is where Mivada’s practice began, and it’s a natural entry point into Databricks. We connect Workday, including Workday Data Cloud, alongside payroll, finance and RPA systems, so workforce data sits inside the same governed Lakehouse as the rest of the business.
Yes. Our consultants design Unity Catalog governance structures, including lineage, data quality frameworks, and access and permissions modelling, so governance scales with usage instead of being bolted on later.
Let’s turn your data platform into a foundation your business can act on
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