Raw data
to the concrete impact
By combining your industry expertise with our know-how, we reveal the performance drivers of your company.
Data Engineer
Structuring of reference frameworks
Implementation of quality and compliance
Access control and cataloging
Setting up BI environments and/or data scientist exploration
We have deployed analytical environments tailored to business needs and data scientists:
* BI: design of decision-making dashboards (Power BI, Tableau) for finance, market or production.
* Data Science: setting up secure working environments (Databricks, MLflow, Jupyter) to train and industrialize models (prediction of industrial failures, detection of weak signals in health insurance).
👉 Skills: Modern BI, secure environments for data science, MLOps, governance of analytical environments.
Data engineering in the aforementioned technologies
We operate across the entire data cycle, with expertise in leading technologies:
* Cloud: Azure (Data Factory, Synapse, Databricks), AWS (S3, Glue, Redshift), GCP (BigQuery).
* Distributed storage & computing: Hadoop → CDP, Spark, Kafka.
* Modeling: design and optimization of pipelines for data ingestion, transformation and valorization.
* Use cases: HDP → CDP migration in a hospital, implementation of Big Data pipelines for Michelin connected tires, IoT integration for healthcare projects (connected pen).
Problems, optimization, costs, performance
Agaetis has helped several clients reduce their costs and improve their production performance:
* Cloud FinOps: 10% reduction in operating costs in healthcare (HDP → CDP migration).
* Energy optimization: ML algorithms to reduce consumption and anticipate industrial machine failures.
* BI/Reporting: optimization of Power BI queries and environments to improve response times and reduce infrastructure costs.
* Skills: technical audit, FinOps, performance tuning, ML for optimization.
Data design
We support organizations in the design and structuring of their data:
* Data governance: implementation of catalogs, repositories and annotation processes.
* Data by Design: integration of security, compliance and scalability principles from the design phase.
* Advanced modeling: design of Big Data and AI solutions.
* Skills: business modeling, DWH design, Data Vault, data lineage, quality and integrated governance.
Concrete results, driven by the power of data





