Driving tests produce an enormous amount of measured data for different development disciplines. Some companies have therefore begun to collect these data in a so-called “Data Lake”.
At the heart of such a “Data Lake” is usually the open source platform Hadoop. It provides a variety of frameworks that enable to process and analyze the incoming data volumes flexible in manifold ways.
Continue reading “ToDo´s to extend ASAM ODS to Big Data”
Measurement data must be quickly retrievable, comparable and interpretable for different purposes and by different persons even after a long time. Companies can only achieve this by precisely documenting under which conditions (= context) the respective measurement data have been created. Conclusion 1: Transparency on test data becomes problematic, if measurement files are stored on the hard disk of a local computer or server just based on individually selected names without a detailed description.
That´s why the market offers a whole series of software tools with which this file-based storage of measurement data can be better organized.
Continue reading “Standardization and transparency in the test environment”
