Improving quality while reducing time, effort and cost
Effectively developing and/or implementing new application environments requires a complete understanding of the legacy data sources impacted. In most cases, however, solid knowledge of all sources is not available, and can be viewed as cost or time prohibitive to obtain. As a result, data migration is almost always the least understood, most poorly scoped, and therefore most expensive and resource-intensive part of a new application deployment project.

Yet, going forward without a complete understanding or choosing not to migrate legacy data inevitably leads to unanticipated issues, resulting additional time, expense and effort to finish the project.

Holistic view of legacy data
By automatically identifying the schemas of and field-level relationships within and between data sources, Harvester enables an organization to have a complete and accurate picture of all impacted data assets very early in the project lifecycle. This includes determining which data elements exist where and how they are related across an enterprise full of disparate systems, as well as the relative "quality" of these related elements.

Completing this analysis also provides organizations with a virtually centralized view of the data sources. Sypherlink's Exploratory Warehouse provides a single, virtual schema through which you can interact with data from the disparate source systems for prototyping and querying.

The results of the Harvester analysis and Exploratory Warehouse allow an organization to better scope and plan the migration process, saving a tremendous amount of time, money and effort. In later phases of project, there are many additional ways that the results can be leveraged.

Adding value every step
In addition to streamlining the data migration process, Sypherlink's product suite delivers further efficiencies throughout the project to ensure successful implementation of a new application.

Data gap analysis and data model design
In a new application implementation, Harvester is used not only to discover where the different data elements exist (and may be duplicated) across the legacy applications, but the resulting information can also serve as the foundation for the creation of the data structure/schema required for the new application. The results can also be used to verify that the new application "has a place" for all existing data elements and that the legacy applications contain the data elements for all of the required fields in the new application.

Data quality
Data quality analysis allows the implementation team to fully understand quality issues sooner in the project, eliminating costs and reducing planning errors. Sypherlink's Integrity can be used to identify data quality and normalization issues that must be addressed during the migration process. Arbiter will also recommend normalization steps that can be applied to your original source data or that can be completed as part of the ETL process.

Rapid, virtual prototyping
Exploratory Warehouse's prototyping ability shortens the design and development or configuration phases of the project and allows you to verify that the planned systems match the business needs before expensive customizations or configurations take place, and reduces or eliminates the possibility of expensive "re-work" later in the process. Once the new application is fully implemented, the unique capabilities of Exploratory Warehouse enable simultaneous access to all of your production systems in order to facilitate consolidated access to physically disparate data assets.

Extraction, transformation and load
Choosing Sypherlink to complement your ETL application simplifies your integration environment. Sypherlink’s field-level mapping relationships can be seamlessly integrated into leading ETL applications, making integration simple and transparent. Regardless of the combination of tools, Sypherlink’s technology accelerates the implementation; reduces risk, cost and resources; and maximizes value of development and reengineering efforts.