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Enterprise Data Hub: Development and Integration

Financial sector

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Enterprise Data Hub: Development and Integration

Customer International Bank
Industry Financial services
Scale 5000+

Creation of a multifunctional center for aggregation, processing and presentation of data along with secured real-time exchange of enterprise data. Scalable architecture for real-time data exchange, 24/7. The number of processed events is about 2-3 million per day and up to 200 events per second. 


The solution’s capabilities included real-time message exchange and trigger-driven push notifications, enhancing customer interactions and engagement. It leveraged real-time communication to offer additional services and updates from open databases and registries. The architecture facilitated cost-effective storage of archive data while ensuring the concurrent processing of event flows, making data accessible to various business applications. It addressed security and data quality requirements, ensuring compliant data access for end-users.


EDH allows the collection and analysis of data from numerous sources, which is crucial for comprehensive analysis.

Utilizing tools such as Apache Hadoop, Apache Spark, Hive, Flink, and NiFi, Dataslab EDH offers robust capabilities for big data processing.

The solution supports the growing needs of enterprises in data analysis, providing scalable data processing and flexible integration, both for working with historical archives and for streaming data online.

Dataslab EDH provides comprehensive tools for building a subsystem to track key performance indicators and generate reports, aiding in informed decision-making.



EDH is an essential tool for enterprises aiming to enhance the efficiency and quality of their analytical processes. The innovative software solution for on-premises data processing and analysis. This solution harnesses cutting-edge big data processing and machine learning technologies, delivering unparalleled efficiency and accuracy. It’s the perfect fit for companies seeking to deeply understand their data, providing rapid processing speeds, user-friendly tools, and flexible integration with existing systems.

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