Unlock the full potential of your data with Microsoft Azure

Build a modern data foundation with Azure Databricks and Azure Data Lake Storage. Datumo designs and implements Lakehouse architectures that unify structured and unstructured data into a single source of truth - enabling seamless data exploration, real-time analytics, and secure collaboration across your organization.

Our Azure Lakehouse solutions deliver:

• scalable data storage and compute optimized for performance and cost,
• native integration with Power BI and Microsoft Fabric for self-service analytics,
• governance and access control through Unity Catalog and Azure policies,
• automation of data ingestion, transformation, and management pipelines.

Use Azure Machine Learning as the central hub for training, evaluating, and deploying ML models. Leverage AutoML, managed compute clusters, pipelines, and custom training flows. Integrate Azure OpenAI Service and other Azure AI Foundry capabilities to build powerful, production-grade AI applications that deliver real business impact.

Create reliable, automated ML operations with experiment tracking, dataset/model versioning, pipelines, and monitoring. Implement CI/CD with GitHub Actions or Azure DevOps to ensure reproducible deployments and controlled rollouts. Keep models continuously evaluated, retrain when needed, and maintain full auditability across the lifecycle.

Our MLOps solutions provide:

• reproducibility and governance across teams,
• automated experiment tracking and versioning,
• seamless integration with DevOps and observability tools,
• faster time-to-market for machine learning applications.

Build scalable, automated, and well-governed data pipelines with Datumo’s modular frameworks for Azure Databricks and Apache Airflow.
We design and implement data engineering ecosystems that accelerate data movement, transformation, and integration - connecting all your data sources into a single, trusted environment.

Our Databricks framework provides a standardized and reusable foundation for developing and deploying Apache Spark-based ETL, ELT, and Data Quality pipelines.
It ensures consistency across environments, simplifies monitoring, and integrates seamlessly with CI/CD and Unity Catalog for full lineage and governance.

In parallel, our proprietary Airflow deployment on Azure Kubernetes Service (AKS) offers a scalable and secure orchestration layer for both batch and streaming workloads.

We extend Apache Airflow with best practices for modular DAG structure, centralized logging, alerting, and continuous delivery - ensuring reliable and auditable data operations.

By combining Databricks for data ingestion and processing with  Airflow on AKS for orchestration, Datumo delivers a robust, automated, and cloud-native data engineering platform that grows with your business.

Turn connected devices and sensor data into actionable insights with Azure IoT solutions designed and delivered by Datumo.
We build IoT data platforms that connect, process, and analyze real-time data streams using services such as Azure IoT Hub, Event Hubs, and Stream Analytics - ensuring secure, scalable, and low-latency data flow from edge to cloud.

Our IoT architectures combine event ingestion, data transformation, and real-time analytics with downstream integration into Azure Databricks, Data Lake, and Power BI - enabling unified visibility across operations.

Datumo’s approach ensures:

• reliable connectivity and data ingestion from thousands of devices via Azure IoT Hub or Azure Kubernetes Service,
• low-latency processing and event routing with Event Hubs and Stream Analytics,
• automated data enrichment and persistence in Azure Data Lake or Lakehouse environments,
• actionable dashboards and predictive insights powered by AI and Azure Machine Learning.

From smart manufacturing and logistics to energy monitoring and connected retail, we support enterprises in using IoT data to optimize operations, predict issues before they occur, and create new revenue streams.

Create real-time data systems using Azure Event Hubs, Azure Stream Analytics and Azure Data Explorer. Process events with low latency, feed operational dashboards, detect anomalies, and power personalization engines. For advanced streaming logic, use Databricks and Spark Structured Streaming. Autoscaling ensures smooth performance even under unpredictable workloads.

Datumo helps enterprises build real-time processing pipelines that handle thousands of events per second - supporting use cases such as:

• fraud detection and risk scoring,
• IoT data analysis and telemetry,
• customer behavior tracking and personalization,
• operational monitoring and alerting.

Transform your legacy systems into a modern, cloud-native data platform.
Datumo supports every stage of your migration to Microsoft Azure - from strategy and architecture design to data transfer, optimization, and validation.

We ensure a seamless migration process that:

• minimizes downtime and preserves data integrity,
• adapts workloads for Azure-native services such as Azure Databricks, Azure Kubernetes Service or Azure Data Lake Storage,
• reduces operational costs by replacing manual infrastructure with serverless, automated solutions,
• unlocks immediate access to advanced analytics and AI capabilities.