On July 15th, Sypherlink announced the new release of Harvester 5.0. Harvester 5.0 automates the data discovery and mapping process to help organizations save time within the data integration process. The business benefit is simple. Between mergers and acquisitions, regulatory compliance, security, and the need to move data across disparate systems for reporting and analysis, using Harvester can save organizations time and money. Sypherlink’s goal is to accelerate the process required to share data across the organization. By automating a very time consuming part of the process, their products complement the full data integration and analysis process.
How it Works
Sypherlink automates the data discovery and mapping process. Within any data integration or data migration project, organizations require resources to manually identify data sources, data targets, and how they interrelate. Once this process is complete, organizations can effectively transfer, merge, and integrate disparate data sources that are required to help manage various business activities. The process itself is very time consuming and requires subject matter experts who know how the organization’s data interrelates and where it resides.
Harvester 5.0 identifies data, metadata, primary and secondary keys within source and target data. Once this information is collected, the application identifies the probability of relationships between the disparate data sources based on parameters set by the user. Using an automated patented heuristic engine, data is fed back to users to review and validate data relationships. End-users can look through sample data to help identify the validity of the connections and approve the mappings or identify exceptions. Once the mappings are identified and the data is combined in the target database, ETL (extract transform and load) processes are used to load the data into the target database. This includes populating data within Oracle, Teradata, IBM, and business intelligence applications.
Some Features of the New Release Include:
- Discovery capabilities with additional data profiling metrics, database statistics, and metadata to increase process efficiencies
- Enhanced heuristics, including user-selectable name and data matching and user-defined weighting to help with overall match ratings
- A new user interface with point-and-click control of analysis options and feedback to identify project status and to report project progress
- Enhanced user interface design screens that allow definitions of ETL instructions that can be leveraged by supported ETL tools (these include Informatica, Cognos, Business Objects, IBM, etc.) and integrated earlier within the entire data mapping and integration process
- The ability to aside individual mapping and ETL tasks while aggregating sub-tasks into the overall project and generating ETL specifications documentation
Although data integration activities fall outside the general scope of executive interest, saving costs does not. Applications that reduce labor-intensive activities help quicken general project lifecycle activities and free up valuable resources for other projects, tasks, and maintenance. However, using applications that automate processes does not exclude the involvement of subject matter experts. For example, Harvester still requires human intervention to approve or edit relationships and to finalize data mapping relationships.
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