Clean-up and Harness Your Legacy Data
Reduce Costs and Risks to the Enterprise
To neutralize costs and risks, organizations must perform “legacy data clean-up” and implement a proper filing plan to classify documents. This action fosters “defensible disposition” which ensures the method of disposing of unneeded data can be presented in court as reasonable and consistent. When properly implemented, these methodologies can also be used for better knowledge management and to implement other strategic goals.
Watch the Legacy Data Clean-up video »
ZyLAB software enables organizations to include the content stored within obsolete databases or legacy systems in their go-forward initiatives for strategic information management. The ZyLAB system captures legacy data from any number of proprietary ERP, HRM, DMS, RMA or BPM systems and offloads it to an open and sustainable ZyLAB XML archive. The united and standardized content becomes just as accessible and searchable as new files added to the system today.
The Legacy Information Clean-up Process
Every Legacy Information Clean-up process starts with determining which content your employees and systems should use and which they should not. The steps to analyze the data are very similar to the steps implemented in the eDiscovery process:
- Reporting of results (classification, timelines)
- Advising on actions (do nothing, retain or transfer).
Features & Functions
- Deployed in-house as well as hosted (cloud-based) on a fully parallel and distributed Virtual Machine architecture.
- Conversion to XML
- Integration with records management
- Process also includes purely unstructured data like email
- Add retention tags afterwards instead of upfront to save on resources, cost and efficiency
- Add searchable key fields and metadata
- Automatic indexing
- Advanced search tools including advanced text, audio and image search in combination with text mining, content analytics and data visualization
- Retain links to native formats
- A solid legally-defensible methodology including templates, a well-documented quality control methodology, and referenceable case law.
- Reduced storage costs; Save storage space (and backup systems, tapes, time, etc.) by cleaning up redundant, duplicate, old, private and irrelevant data from corporate storage locations and repositories.
- Limit legal exposure by implementing a defensible data retention process.
- Share valuable knowledge as part of knowledge management initiatiaves.
- Clean-up legacy data to prevent compliance problems and eDiscovery and investigative exposure for the long-term.
- Monitor legally risky data streams to prevent compliance problems and eDiscovery and investigative exposure.
- Eliminate file conversions and the need to upgrade proprietary databases.
« Return to ZyLAB Enterprise Information Management System Overview