Lower costs and reduce downtime with predictive maintenance.
Predictive Maintenance is a data-driven approach to analyze IoT and sensor data from connected equipment to effectively predict when and how an asset might fail, detect variances, understand warning signals, and quickly identify patterns that might indicate a potential breakdown. Cloudera DataFlow’s Edge and Flow Management capabilities modernize and simplify data ingestion from hundreds of connected assets to enhance predictive maintenance.
Capture real-time feeds from patient-monitoring devices to detect anomalies.
Biometric and telemetric devices are used in healthcare organizations to monitor post-surgery or high-risk patients. Ingesting sensor data from these devices about various patient vitals helps detect abnormalities or concerning patterns. Cloudera DataFlow’s Edge and Flow Management helps capture patient-monitoring data and delivers them to stream-processing engines for insights.
Connect, integrate, and move massive volumes of data across hybrid and multi-cloud environments.
Traditional ETL processes are for use cases where data must move from one database to another. Modern enterprises transfer data from on-premises to cloud or cloud-to-cloud, moving petabytes of information in a matter of just hours. Cloudera DataFlow’s Flow Management capabilities are purpose-built for such use cases.
Flow Management for Data Hub
- Spin up NiFi and NiFi Registry into your public cloud with Flow Management for Data Hub
- Choose your cluster size (S/M/L) and launch it across AWS, Azure or GCP
- Extend the same on-premises user experience into the public cloud
DataFlow for the Public Cloud
- Monitor all NiFi flows across multiple cloud clusters from a single dashboard
- Boost productivity by leveraging pre-built NiFi flows from a gallery of ReadyFlows
- Optimize the infrastructure sizing by allowing the DataFlow experience to auto-scale the NiFi flows