Azure Databricks Consulting Services

Unlock the full potential of big data and AI with Azure Databricks.

AGER BI helps you design, build, and optimise data engineering and machine learning solutions that unify your data architecture and accelerate insights.

Organisations we’ve helped

What we’ve helped our clients achieve

0M

In savings and new value unlocked

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Data projects delivered with lasting business impact

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Years of solving complex data challenges

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Users supported across Australia and New Zealand

Azure Databricks Consulting Services

Data Engineering & ETL Pipelines

Design scalable data ingestion and transformation workflows using Databricks and Delta Lake for high-volume, low-latency processing.

Lakehouse Architecture Design

Build unified architectures that combine the flexibility of Data Lakes with the structure of Data Warehouses for simplified analytics.

Machine Learning & AI Integration

Use Databricks MLflow to train, track, and deploy machine learning models efficiently and reproducibly.

Data Optimisation & Performance Tuning

Improve query speeds, cluster performance, and cost efficiency through intelligent caching, partitioning, and job orchestration.

MLOps Implementation

Automate end-to-end model lifecycle management with MLflow and Azure DevOps integration.

Integration with Azure Ecosystem

Connect seamlessly with Data Factory, Synapse, Power BI, and Azure ML for a complete analytics pipeline.

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What Azure Databricks Enables

Unified Data Engineering & Analytics

Bring data engineers, data scientists, and analysts together on a single collaborative platform.

High-Performance Data Processing

Handle massive datasets with distributed Spark clusters optimised for Azure scalability.

Delta Lake for Reliable Data Pipelines

Ensure data reliability, consistency, and ACID transactions with Delta Lake storage technology.

Seamless Integration with Azure Stack

Natively connect to Data Lake, Synapse, Power BI, and Azure ML for an end-to-end data ecosystem.

Real-Time Data Streaming & Analytics

Process and analyse streaming data in real time using Structured Streaming and Auto Loader.

Built-In Machine Learning Frameworks

Train and deploy ML models faster using MLflow, AutoML, and integrated libraries for TensorFlow and PyTorch.

Collaborative Notebooks & Version Control

Empower teams to code, document, and visualise together with shared notebooks and Git integration.

Optimised Cost & Resource Management

Dynamically scale compute clusters up or down to control costs while maintaining high performance.

Future-Ready Lakehouse Foundation

Build a scalable Lakehouse architecture ready for Microsoft Fabric and next-generation analytics.

How We Deliver

And here’s how we deliver Azure Databricks for your organisation

1: Discover / Access

Review existing data architecture, workloads, and performance requirements.

2: Design / Blueprint

Define Lakehouse architecture, cluster configurations, and governance model.

3: Build / Deploy

Develop ETL pipelines, ML workflows, and integration with Azure services.

4: Optimise / Automate

Tune workloads, implement DevOps automation, and enhance scalability.

5: Support / Evolve

Provide ongoing optimisation, cost management, and advanced analytics enhancements.

Unified Analytics Platform

Delta Lake Reliability

Real-Time Streaming

MLOps Integration

Cost Efficiency

Collaborative Development

Security & Compliance

Azure Ecosystem Integration

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How we deliver results

Your trusted certified Microsoft experts

Microsoft Azure Data Engineer Associate logo

Microsoft Azure Data Engineer Associate

Microsoft Power BI Data Analyst Associate logo

Microsoft Power BI Data Analyst Associate

fabric analytics engineer logo

Fabric Analytics Engineer Associate

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Databricks Associate Developer for Apache Spark 3.0

We are certified specialists in Microsoft platforms such as Power BI, Fabric, Azure Data Factory, Azure SQL Database, Azure Synapse Analytics and Azure Databricks. We are also experts in Qlik View, Qlik Sense, Snowflake and Tableau.

What Azure Databricks Can Do For Your Business

Number 1

Simplify Data Engineering at Scale

  • Azure Databricks provides a single, powerful platform for building scalable data pipelines that integrate seamlessly with Azure Data Factory and Data Lake. By unifying data ingestion, transformation, and modelling under one environment, your teams can process terabytes of data faster, maintain cleaner data pipelines, and reduce reliance on manual ETL maintenance.

Number 2

Deliver Faster Insights with the Lakehouse Architecture

  • Databricks’ Lakehouse approach combines the flexibility of a data lake with the performance of a data warehouse. This unified architecture allows business users to access both structured and unstructured data instantly, enabling real-time reporting and analytics through Synapse and Power BI, without complex data duplication or movement.

Number 3

Boost Collaboration Across Teams

  • Break down silos between engineers, data scientists, and analysts. Databricks’ collaborative notebooks allow teams to share code, visualisations, and insights within a common workspace. Built-in version control, documentation, and commenting features foster transparency and teamwork, leading to faster delivery and better outcomes.

Number 4

Operationalise AI and Machine Learning

  • Move from experimental models to enterprise-grade AI solutions. With MLflow built into Azure Databricks, you can track experiments, manage model versions, and automate deployments. This makes it easy to scale your machine learning efforts, ensuring every model is reproducible, governed, and continuously improving.

Number 5

Reduce Costs with Elastic Compute Scaling

  • Databricks automatically scales compute clusters based on demand, ensuring you never pay for idle resources. Whether processing daily batch jobs or running large-scale analytics, its elastic compute model delivers consistent performance while maintaining cost efficiency, ideal for businesses managing variable data workloads.

Number 6

Culture Improve Governance and Security

  • Safeguard your data assets with Azure’s enterprise-grade security and compliance framework. Databricks integrates with Azure Active Directory, supports role-based access control, encryption, and private networking. Combined with Purview for governance, it ensures your entire data estate remains compliant with ISO 27001, SOC 2, and other regulatory standards.

How Azure Databricks Is Used Across Teams and Industries

Finance

Build scalable fraud detection and credit risk models with MLflow and Spark.

Mining & Resources

Analyse IoT sensor data and production logs in real time for operational efficiency.

Healthcare

Process patient and clinical data securely for advanced analytics and AI-driven diagnostics.

Education & Government

Create unified data environments for transparency, policy modelling, and resource planning.

Manufacturing

Optimise production quality and predictive maintenance using Databricks ML pipelines.

Retail

Build scalable fraud detection and credit risk models with MLflow and Spark.

FAQ

Azure Databricks is a unified analytics platform for big data processing, machine learning, and AI.

Synapse focuses on analytics and reporting, while Databricks specialises in data engineering, AI, and real-time processing.

Yes. Databricks integrates directly with Azure ML for advanced model training, tracking, and deployment.

Absolutely. Databricks supports streaming data ingestion and real-time processing through Spark Structured Streaming.

We architect, deploy, and optimise Databricks environments, ensuring performance, cost-efficiency, and seamless integration with your analytics stack.

Unlock the full potential of your data

Let’s talk about how we can help you get better visibility, better reporting, and better results from your data.

1300 381 500

info@agerbi.com.au