Databricks consultants
We can help you automate your business with Databricks and hundreds of other systems to improve efficiency and productivity. Get in touch if you’d like to discuss implementing Databricks.
About Databricks
Databricks is a unified data analytics and AI platform built on Apache Spark that brings together data engineering, data science, and machine learning in a single collaborative environment. It handles everything from raw data ingestion and transformation to model training and deployment — which means your data team can work in one platform instead of stitching together five different tools.
For Australian businesses sitting on growing volumes of data — customer transactions, operational logs, IoT sensor feeds, marketing data — Databricks provides the infrastructure to actually do something useful with it. Its lakehouse architecture combines the flexibility of data lakes with the performance of data warehouses, so you get both cheap storage and fast queries without maintaining two separate systems.
Where Databricks connects to our work at Osher is in the automation and integration layer. Raw data sitting in a lakehouse is only valuable if it feeds into business processes. We help businesses connect Databricks outputs to downstream systems — triggering AI agents based on model predictions, feeding analytics into dashboards, or piping processed data into CRMs and operational tools through system integrations. The platform is powerful, but the value comes from what you do with the results.
If your data infrastructure has outgrown spreadsheets and basic SQL databases, or if your data team is spending more time on pipeline maintenance than actual analysis, Databricks is the kind of platform that consolidates that complexity. Paired with automated data processing workflows, it becomes the analytical engine driving decisions across your organisation.
Databricks FAQs
Frequently Asked Questions
Common questions about how Databricks consultants can help with integration and implementation
What is Databricks used for in a business context?
How does Databricks differ from a traditional data warehouse?
Can Databricks integrate with our existing business tools?
Is Databricks suitable for mid-sized Australian businesses?
What skills does our team need to use Databricks?
How does Databricks support AI and machine learning?
How it works
We work hand-in-hand with you to implement Databricks
As Databricks consultants we work with you hand in hand build more efficient and effective operations. Here’s how we will work with you to automate your business and integrate Databricks with integrate and automate 800+ tools.
Step 1
Assess Your Data Landscape
We audit your current data sources, storage systems, processing pipelines, and analytics tools to understand what you have, where it lives, and what’s not working. This assessment reveals whether Databricks is the right fit and what migration or integration work is needed.
Step 2
Design the Lakehouse Architecture
We design your Databricks workspace structure — data storage layers (bronze, silver, gold), access controls, compute cluster configurations, and connection points to upstream data sources. The architecture is planned to handle your current data volumes with room to grow.
Step 3
Build Data Ingestion Pipelines
We configure automated pipelines that pull data from your source systems into Databricks — databases, APIs, file drops, streaming sources. Each pipeline includes data validation, error handling, and logging so you know exactly what’s flowing in and can trace any issues quickly.
Step 4
Implement Transformation and Analytics
Raw data gets cleaned, joined, and transformed into analytics-ready datasets. We build the SQL queries, notebooks, or scheduled jobs that produce the metrics, reports, and model-ready features your business needs. This is where messy data becomes actionable insight.
Step 5
Connect Outputs to Business Systems
Processed data and model predictions get piped to where they create value — dashboards, CRM fields, automated workflows, or API endpoints. We use integration tools to connect Databricks outputs to your operational systems so insights translate directly into action.
Step 6
Train Your Team and Hand Over
We train your data team on the Databricks environment, covering daily operations, troubleshooting, and how to extend the platform as your needs evolve. Documentation covers architecture decisions, pipeline logic, and maintenance procedures so your team can run things independently.
Transform your business with Databricks
Unlock hidden efficiencies, reduce errors, and position your business for scalable growth. Contact us to arrange a no-obligation Databricks consultation.