AI Use Cases
synvert Accelerators
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Real-time data ingestion enables companies to extract technical or business events from their systems (including IoT, the Internet of Things) and reuse them in operational and/or analytical systems.
Real-time data ingestion enables companies to extract technical or business events from their systems (including IoT, the Internet of Things) and reuse them in operational and/or analytical systems.
Real-time data ingestion aims to view data as events that occur in an organization and that can be accessed in (near) real time for further processing. For this purpose, this data is first inserted (“ingested”) into a target platform. The target platform is either a long-term storage (data lake, database, etc.) or an event streaming platform, which is primarily designed for further distribution. Real-time data ingestion encompasses various technologies such as change data capture (CDC), Internet of Things (IoT) or sensor data. In a broader sense, this can also include micro and web services with technologies such as REST/SOAP.
Use base analysis - analysis of the use cases for real-time data ingestion and the system landscape.
Licensing - support with licensing the product.
Architectural design - embedding in existing architecture.
Follow-up processing - know-how in the implementation of near-real-time follow-up processing with appropriate tools.
Tool selection - selection of a suitable tool taking into account the requirements.
Analytical use cases – create value by defining and implementing near-real-time analytical use cases.
Proof of concept – implementation of a PoC to validate feasibility.
Real-time data ingestion supports your company in mapping the flow of information in your company in real time. With real-time analytics and our experience, we help you to gain valuable insights and make decisions based on real-time data.
No more end-of-day / batch processing, but efficient distribution of events in the corporate ecosystem.
All systems and processes benefit from the prompt provision of data and thus contribute to added value.
Provision of near-real-time information on events for short-term operational decisions.
Timely data can lead to faster reactions and better decisions in a volatile environment.
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