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Efficient Management and Analysis of Measurement Data

Vector vMDM22 May 2018 – vMDM is Vector’s new solution for efficient management of large data volumes from development, bench testing and vehicle testing. Working with a server-based or cloud-based variant, users can perform CPU-intensive analyses of measurement data, create classifications and generate reports. The acquisition of measurement data often requires the involvement of many development teams in a single project in which the data must be merged. vMDM simplifies the sharing and exchange of data between these distributed teams.

 Today’s vehicle developers are dealing with volumes of measurement data not seen before. At the same time, they must speed up troubleshooting and increase the depth of testing. A major challenge is secure storage of the data recorded from test benches, road testing and endurance testing. vMDM is a new software solution for organizing such measurement data into customer- or project-specific collections and assigning user-specific permissions to protect data against unauthorized access. vMDM additionally gives developers a convenient means of searching, filtering and displaying their measurement data. Indexing of measurement results is performed automatically during import by the in-house server or in the cloud. In contrast to other solutions, vMDM creates the data index based on freely configurable and extendable attributes. vMDM is scalable as a multi-user system depending on the expected data volume and the required server performance.

 Users of the Vector tools CANape, vSignalyzer and vMeasure exp perform the interactive data analysis of the measurement data stored on the vMDM server on their workstation computer. Thanks to seamless integration of vMDM with these Vector tools, there is no need for users to leave their familiar working environment. They can define scripts, data analytics and data mining functions in the usual manner with these measurement, calibration and analysis tools.

 Starting with vMDM version 2.0, users will also benefit from automatic data analyses and data mining. This will reduce computational load on their PCs. In addition, configurable preprocessing when loading measurement files and automatic creation of statistical reports will be added in the first quarter of 2019.

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