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SDIL Smart Data Innovation Lab

The Smart Data Innovation Lab (SDIL) offers big data researchers a unique opportunity to use a wide range of big data and in-memory technologies.


The Smart Data Innovation Lab (SDIL) offers big data researchers a unique opportunity to use a  wide range of big data and in-memory technologies  . Industry and science work closely together to find hidden values ​​in big data and to generate smart data from them. Projects  focus on strategic research in the areas of Industry 4.0, energy, smart cities and personalized medicine.

TECO is heading Germany’s Big Data Centre, the Smart Data Innovation Lab (SDIL). TECO is associated with the chair of Pervasive Computing Systems group of the Institute of Telematics at the KIT which covers the education activities.


Baden Württemberg / Germany

Infrastructures and services

  1. SAP HANA: The SAP HANA in-memory appliance is available for use on the SDIL Platform.
  2. Terracotta BigMemory Max: BigMemory Max is installed and available on the SDIL Platform. A single and active Terracotta Server is configured and running on this machine.
  3. IBM Open Platform with Hadoop and Spark: The SDIL Platform has the IBM Open Platform available and is running Apache Hadoop on a cluster with IBM Power8-Nodes.
  4. Virtualization and Resource Allocation: In order to use the SDIL resources efficiently and to avoid interference between users, we make use of the HTCondor batch system.

Additonal information

  1. Infrastructure providing: The infrastructure, including technical support, is provided free-of-charge by the SDIL operation partners to any SDIL project.
  2. Communities: SDIL provides access to experts and domain-specific skills within Data Innovation Communities fostering the exchange of project results. They further provide the possibility for open innovation and bilateral matchmaking between industrial partners and academic institutions.
  3. Data curation: The SDIL guarantees a sustainable investment to all partners by curating industrial data sources, best practices, and code artefacts, that are contributed on a fair share basis.
  4. Data Anonymization: The SDIL offers various anonymization tools to its projects which are applicable to data from research and industrial sources.