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.
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.
Companies from a variety of industries already trust Sidra to help them manage their data.
Sidra has helped a multinational online advertisement company modernize their data platform by providing a fully PaaS Azure platform with automated deployment via Azure DevOps. Before Sidra was implemented, they relied on an on-premises platform, with higher costs and lower performance, as well as long times whenever new data sources appeared, and a lot of trouble whenever any data provider decided to update their schemas. Thanks to Sidra, they’re now able to better react to the changing needs of the business and provide a better platform for their clients to draw insights from their vast amounts of data.
Sidra has helped a major travel company with the development and implementation of a data lake platform integrated with their mainframe and Salesforce system, that is capable of manage the growing needs of the company by consolidating information form users and ticket sales and providing it to their existing BI and analytics tools. A subset of the data is processed in real time, providing up-to-date information to the points of sale, as well as a 360 view of their customers
Oil & Gas
Sidra has helped a giant in the energy sector with the development of a data lake platform to allow data sources from across the company (commercial, industrial, laboratories, etc.) to be stored and available, so they can be consumed by a number of company-wide initiatives. These initiatives are able to leverage the stored and processed data, as well as Azure flexibility, to work with the information they need with the tools better suited for the task, including Hadoop/Spark clusters and virtual machines with GPU processing capabilities.
Sidra has helped a retail multinational build a data lake platform that aggregates all available information from products and stores to leverage it in advertising campaigns, indoor tracking or real time surveys. By analyzing historical information, the company can suggest product recommendations and coupons tailored to the interests, needs and shopping habits of different customers.
Thanks to Sidra, a major online banking entity has been able to integrate their data sources (both batch and real-time) into a data lake in Azure, in order to replace its current on-premises systems. In addition, they have leveraged the capabilities of model serving tools to support their advanced users and enable them to work on advanced data analytics use cases in a more agile and easy way.
Sidra has made it easier for a major international law firm process the case-related data they manage, taking advantage not only of the automated ingestion processes of the platform, but also the possibilities offered by the model serving tools to create eDiscovery models that make it easier for both their employees and their customers to access the relevant information.