_
We build and evolve your Lakehouse platform with Databricks,
taking it to the next level through advanced analytics and artificial intelligence.
What is your starting point?
We design with you an architecture based on Databricks’ Lakehouse approach, designed to grow at your pace. We define the governance model, automate processes, and help you deploy an agile, secure, and scalable data and AI infrastructure. An intelligent data platform, with AI integrated in all areas, where data and AI governance are fully guaranteed from the outset.
Our approach combines technical expertise, data governance, and accelerators that minimize risk and maximize return from day one. We guarantee continuity, performance, and a smooth adoption.
Your Lakehouse can do much more.
We optimize performance, unify management, and enable advanced analytics and AI use cases. From workflow automation to the operationalization of Machine Learning and Generative AI, we take your platform to its maximum potential.
We optimize performance, unify management, and enable advanced analytics and AI use cases. From workflow automation to the operationalization of Machine Learning and Generative AI, we take your platform to its maximum potential.
_
- Direct access to Databricks technical resources.
- Early access to new features and updates.
- Data Engineer Associate & Professional.
- Databricks AWS / Azure / GCP Platform Architect
- Databricks Generative AI.
- Platform Administrator.
- Cloud Native Spark Migration.
- Data & AI Governance.
- Gen AI & LLM on Databricks.
- Design of custom architectures based on Delta Lake.
- Unified and secure governance of data, models, and AI assets with Unity Catalog.
- Smooth migrations and continuous performance optimization.
- Scalability and resilience so that your platform grows with your business.
- Reliable data flows that guarantee availability and consistency in your Lakehouse.
- Design and implementation of ETL/ELT pipelines and streaming flows, maximizing load optimization capabilities.
- Automated and governed processes to ensure data quality and availability.
- Integration with cloud environments and analytical tools.
- Monitoring and operational support to maintain maximum performance.
- Unification of the Machine Learning lifecycle with MLflow and Unity Catalog.
- Unification of the lifecycle of LLM models, both OpenSource and commercial.
- Complete governance of data, models, and features.
- Development and deployment of custom and AutoML models.
- Validation and audit processes for reliable and secure AI.
- Integration from the beginning of LLM models as a judge.
