to drive business outcomes.
Data science starts with data. So, your big data initiative needs all the right pieces: the data lake, the analytic applications, and likely an on-premise/multi-cloud architecture. All that remains is integrating with lightning-fast, scalable, and elastic connections. With Cleo’s big data integration engine, you can move and integrate petabytes of big data.
Consolidate integrations and streamline data flows for centralized control and visibility
Quickly access, integrate, and ingest data of any size or volume without risk of downtime
Gain visibility and insight into all data to eliminate dark data and secure and govern big data flows to comply with business and industry requirements
Cleo delivered the high-availability environment Tungsten Network needed to manage the substantial data transfers for our thousands of global trading partners. Cleo’s truly scalable architecture and advanced visibility features will be invaluable assets for making strategic business decisions and enabling Tungsten’s future growth.
Chris Tallis
Tungsten Network, Director of Technical Services and Operations
• Quickly business and application data flows to your big data storage and analytics systems
• Remove data flow bottlenecks by consolidating internal data silos to build a data lake
• Connect and accelerate the movement of data into data lake repositories
• Securely move data, of any size or volume to S3, Azure, and HDFS without compromising network limitations
• Build highly scalable dataflows and quickly accommodate new integrations
• Ensure 100% system uptime and high availability
End-to-end
Stream data from source to target without having to write to intermediate storage
Consolidation
Connect to all internal data sources to enable easy data lake ingestion
Flexibility
Connect to all data sources outside of your enterprise
Elastic
Easily handle batch data, large volumes of data, and real-time data transfers
Control
Governance layer for development and management for all data sources
Scalability
High availability to support the most demanding levels of throughput