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Big data analysis of driving behavior

The task

For automobile manufacturers, the data-based evaluation of driving behavior has enormous potential to increase customer satisfaction and reduce costs.

The challenge

In order to be able to draw robust conclusions, statistics must be drawn from extremely large amounts of data.

our solution

In this project, a big data analytics environment was therefore provided for the evaluation of mass data in the cloud. The new data stored in the environment via a data loading path is automatically converted into a big data analysis format. Particular attention had to be given here to the adjustment and plausibility check of the data. In addition, created analyzes should be able to be easily converted into regularly executable and programmatically controllable workflows. These requirements were addressed by providing an individually configurable, container-based development environment.

The customer benefit

The solution provided enables analysis teams to have fast, worldwide access to the data shortly after they have been created.



Our role

Support of the customer by data scientists and data engineers

Our activities

  • Setting up a big data / Hadoop environment in the cloud

  • Set up big data workflows to convert data

  • Creation and production of measurement data analyzes

Technologies & methods

  • Applications: DaSense

  • Databases / databases: Hbase, MF4, Parquet

  • Languages / Frameworks: Python (Anaconda Stack), Java, Javascript, Hadoop / Azure, HDInsight, Spark, Yarn, Oozie, Docker Swarm

  • Methods: time series analysis

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