More organizations are adopting data lakes as part of their architecture for their low cost and efficiency in storing large volumes of data. The idea is simple: Instead of storing data in a purpose-built data store, you move it into a data lake in its original format. This eliminates the upfront costs of data ingestion and transformation. Once data is in the lake, it’s available to everyone in the organization for analysis.
Initial on-boarding of data from multiple sources
Continual updates in real-time
Moving high volumes of data to the data lake while mitigating chatter and latency
Accelerate data movement with minimal impact on systems
Efficiently load and update data
Scale the solution for multiple projects and systems
Move high volumes of data for real-time analysis
 | Key Features: See how change data capture, data validation and repair, and reporting all in one tool simplify data integration management. |
 | Table Creation and Initial Load. Mapping data between source and target is automated and made easy. |
 | Log-Based Change Data Capture. Only the changes are moved between source and target, a low impact way to move data. |
 | Data Compare. Have assurance your data is accurate. HVR includes the ability to compare data before consumption. |
 | Insights: This tool gives you the ability to view how data is moving in real-time, be proactive and identify chokepoints. |
HVR 5.2: Data Lake HVR 5.2 provides even faster, more secure, and accurate data movement in a modern environment. Latest enhancements include features that help customers optimize their adoption of data lake technologies. Read on to learn more… Defining Data Lakes...