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Legacy System Conversion & Integration

Modernizing Equipment
& Operating Systems

Legacy System Conversion becomes necessary or desirable when newer technology provides sufficient benefits or requirements that make older platforms and data no longer economically feasible to maintain.

Legacy System Conversion is the process of creating programs and operating procedures for the manipulation of data repositories that are to be utilized in an application or platform of a different standard. Typically, an organization has amassed substantial information and resources in a database and desires to carry the data forward to be used in a new application. Legacy System Conversion will provide the benefit of an organization migrating its data as its business evolves.

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WHAT WE IMPROVE

Bringing Operations
Up To Current
Standards

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Security of Operating Systems Connected To The Internet

Speed Of Operation With Modern Equipment

User Experience With Updated Interfaces

Access To New & Old Data

In our Legacy System Conversion consulting and implementation efforts, we carefully analyze and consider each of these factors in designing the best overall solution with the lowest TOTAL cost of ownership for our clients.

Legacy System Conversion is not a one-time event. As new applications are developed and deployed there will always be an issue with the data from the previous system. By using careful planning and technical experience, Data Science Automation can help your organization move its data forward as new applications and needs are discovered.

 

What We Perfect

LabVIEW Version Upgrades

Hardware Obsolescence

Database Migration

Operating System Upgrades

System 
Compatibilities

User
Accessibility

Language
Localization

Scalable Data Infrastructure

DAQ/PLC/PAC

HMI/SCADA

FPGA

PharLap

Communication
Buses

Data Transmission Protocols

Sensor
Integration

Hardware/Software Compatibilities

Firmware
Upgrades

Cloud
Computing

Technology
Advances

System Compatibility Expansion

Get Started Today

Robust, modular test system architectures can result in short test development times and higher test capacities; and with more products getting tested sooner, more products will be sold and shipped. High throughput testing for pass/fail results is a worthy goal, but so much more can be accomplished. Data Science Automation extends the test strategy to automated text, web and database reporting, and ultimately to process improvements focused on defect prevention.

Would you like one of our Automated Test experts to contact you to discuss your application?