A solution for Enterprise Data Lake Scenarios with a focus on deploying a working system quickly while providing scalability and ease of maintenance.

Sidra Data Platform is a data lake platform built on Azure PaaS. It is an enterprise data lake solution focused on deploying a working system quickly, facilitating scalability throughout the lifecycle of the platform and simplifying every action related to maintenance.

Sidra is an automated and customizable platform with the capability to process large amounts of data regardless of its source. It offers, among other features, the possibility of storing data in multiple regions in a transparent way, an integrated data catalogue service, data lineage control, consolidated view of logs and audit, as well as a comprehensive set of associated services and extensibility APIs.

Sidra provides the common foundation, shared services and governance of the data on which organizations build their specific use cases; from analytical applications based on SQL Server and Power BI, to scenarios of exploratory analysis and generation of machine learning models using Databricks and MLFlow.


Accelerate the launch of your enterprise data lake and reduce costs thanks to the Sidra data platform.

Benefits of Sidra

  • Full deployment in less than 24 hours
  • Automation of data source configuration gets you from zero to data lake in hours
  • Modular and adaptable to each scenario (real-time, ML model serving, web interface…)
  • The Data Catalog and governance capabilities can help address the data protection regulations challenges

Sidra Data Platform Features

  • Automation of ETL/ELT process through automatic generation of pipelines for loading, movement and data processing.
  • Multimodal storage supporting all types of data sources: from databases and APIs to documents and media files.
  • Web interface for platform management.
  • Internal data warehouse and operational dashboards for monitoring all data movements in the system.
  • Reduction of time-to-market thanks to automated deployments and updates, supported by self-generated CI/CD pipelines.
  • Support for multiple storage regions.
  • Integrated infrastructure and platform logs through Azure Log Analytics.
  • Complete Data Catalog with web UI and API access, as well as data lineage audit and traceability.
  • Ability to attribute the costs of each consumer application to different cost centres.
  • APIs for the integration of third-party tools in areas such as Data Catalog or Data Retrieval, as well as Python SDK for Data Scientists.
  • Identity management via Identity Server, allowing secured access to the platform to users with different authentication providers (Azure Active Directory, Google Accounts…).
  • Model Serving Platform to enable your Data Science teams to build, test and deploy  secure models, while tracking both code and training data for audit and explainability purposes.
  • Pre-packaged ML models that tackle the most common challenges during the data load process, such as corruption or anomalies in the data set, as well as automatic detection of PII sensitive data.
  • Support for both batch and real-time data loads, enabling operational data lake scenarios.
  • Predefined consumer applications for data quality and Data Labs scenarios through notebooks in Databricks.

Our Clients


Companies from a variety of industries already trust Sidra to help them manage their data.

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