Precisely Data360 for Kafka
Precisely Data360 for Kafka delivers streaming data with producer-to-consumer validation
As the volume and velocity of data continues to grow, streaming data represents a paradigm shift that introduces new data quality challenges.
The speed of business today demands that organizations enable access to real-time data. This has given rise to event-driven architectures. This fundamental shift from batch processing to streaming data provides new opportunities for increased data delivery reliability, more nimble reactivity and faster business insights. But it also presents new risks to data integrity as streaming sources, data volumes and architectural complexity continue to grow, affecting data reconciliation.
Among the many streaming data options, distributed streaming platform Apache Kafka has become the preferred software for real-time data communication. However, while Kafka is an agile, high-throughput, low latency option for managing data in motion, it cannot ensure the reliability and accuracy of real-time data streams which present many data quality challenges.
Read more about Precisely Data360 for Kafka and how it delivers trust in streaming data with producer-to-consumer validation and reduces enterprise risk by ensuring that streaming data is validated, reconciled, and timely, to produce meaningful and reliable data insights.