AVL List GmbH and NorCom Information Technology GmbH & Co. KGaA are the first companies to offer a portfolio that supports the Big Data feature introduced in the new ASAM ODS 6.1.0 standard, providing the automotive industry with an open and seamless data intelligence solution. Its major advantage is the combined strengths of all involved products, coupled with AVL’s expertise in powertrain and vehicle development.
The member companies of the organization ASAM (Association for Standardization of Automation and Measuring Systems) are involved in the development of technological standards for the automotive market. The so-called ODS (Open Data Services) standard focuses on the persistent storage and retrieval of testing data. Being a partner of the ASAM consortium, AVL has contributed significantly to the specification of the standard. The same is true for the latest version of ODS, which deals primarily with the integration of Big Data platforms. AVL’s ODS server, Santorin MX, is the first ODS server to support the ODS Big Data standard. The interface developed by NorCom, which is based on it, will open the door to a new dimension of measurement data analytics. All of the listed features are available in AVL and NorCom’s product portfolio:
- Scalable conversion of all automotive data formats in the new Avro Packed and Parquet Packed/Point schema, allowing the examination of all data, including Big Data
- Analysis libraries to simplify the use of advanced analytics algorithms and methods in conjunction with automotive-specific analysis packages
- Integration of comprehensive full-context search services to uncover realtime data insights into all data: from process information, measurement meta-data, mass measurement data and results of scalable analysis queries
- Integration and export functions to allow available processing tools to access and process analysis results, and to enable the use of real-time searches of all the relevant data sources.
AVL and NorCom incorporate their extensive knowledge and time-honed best practices straight into their product portfolio, resulting in products that offer efficient solutions to the challenges of R&D and engineering. Engineers can take full advantage of the performance capability of Big Data, even without requiring complete knowledge of Big Data technologies or frameworks.
SOURCE: AVL
