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Sidra Data Platform

Accelerate your data journey

Deploy an Enterprise Data Platform on Microsoft Azure in just one day.

A modern framework for agile development of complex data projects

Sidra is a PaaS data platform targeted at system integrators and consultancy companies, empowering developers with a robust framework that accelerates the development and delivery of data projects for customers.

Sidra is deployed directly within an Azure Subscription, with all critical processes executed in this context. This approximation ensures that data never leaves the customer’s cloud premises, providing a clear advantage against traditional SaaS solutions that is highly valued by enterprise customers who need to retain control of their key processes.

What are the advantages of Sidra?

  1. 1

    Up to 80%** less delivery time and implementation cost

    Through automated deployment processes for Azure and Databricks assets organized in logic blocks, combining sound architecture patterns with reliable code. This approach allows Sidra to deliver full features such as Data Governance, Security, Compliance, Observability and Data Quality with greatly reduced complexity as part of our ready-to-use solution.

  2. 2

    Reduced failure occurrence, increasing data availability

    By leveraging our pre-engineered building blocks, out-of-the-box data ingestion processes, and Azure's PaaS Services, Sidra allows organizations to set up reliable data processes that not only can be managed with ease, but drastically reduce failure rates while increasing data availability.

  3. 3

    Latest security standards with Azure environments

    All these benefits are delivered in compliance with the latest security standards. Your data will always be within your Azure environments in self-contained, managed data storage units that can be set up in different geographic regions with defined access criteria for each one.

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

    Allowing self-service operation for most of the operational aspects of the platform.

  • Internal data warehouse

    And operational dashboards for monitoring all data movements in the system.

  • Support for multiple storage regions

    To enable advanced compliance scenarios.

  • Integrated infrastructure and observability platform

    With automatic configuration leveraging azure artifacts.

  • Complete Data Catalog with web UI and API access

    As well as data lineage audit and traceability.

  • Ability to attribute the costs

    Of each data product instance to different cost centres.

  • Reduction of time-to-market

    Thanks to automated deployments and updates, supported by self-generated

  • 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

    In areas such as Data Catalog or Data Retrieval, as well as Python SDK for Data Scientists.

  • Pre-packaged ML models

    In areas such as Data Catalog or Data Retrieval, as well as Python SDK for Data Scientists.

  • Support for both batch and real-time data loads

    Enabling operational data platform scenarios.