Abstract
Industry 4.0 and the Internet of Things are recent developments that have lead to the creation of new kinds of manufacturing data. Linking this new kind of sensor data to traditional business information is crucial for enterprises to take advantage of the data’s full potential. In this paper, we present a demo which allows experiencing this data integration, both vertically between technical and business contexts and horizontally along the value chain. The tool simulates a manufacturing company, continuously producing both business and sensor data, and supports issuing ad-hoc queries that answer specific questions related to the business. In order to adapt to different environments, users can configure sensor characteristics to their needs.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Play - The High Velocity Web Framework For Java and Scala. https://www.playframework.com. Accessed 06 Nov 2018
Davenport, T.H., Dyché, J.: Big Data in Big Companies, May 2013. http://docs.media.bitpipe.com/io_10x/io_102267/item_725049/Big-Data-in-Big-Companies.pdf. Accessed 28 Feb 2017
Hesse, G., Reissaus, B., Matthies, C., Lorenz, M., Kraus, M., Uflacker, M.: Senska - towards an enterprise streaming benchmark. In: Performance Evaluation and Benchmarking for the Analytics Era - TPC Technology Conference, pp. 25–40 (2017)
Huber, M.F., Voigt, M., Ngomo, A.N.: Big data architecture for the semantic analysis of complex events in manufacturing. In: 46. Jahrestagung der Gesellschaft für Informatik, Informatik, pp. 353–360 (2016)
Mikowski, M., Powell, J.: Single Page Web Applications: JavaScript End-to-End, 1st edn. Manning Publications Co., Greenwich (2013)
Plattner, H.: A common database approach for OLTP and OLAP using an in-memory column database. In: ACM SIGMOD International Conference on Management of Data, pp. 1–2 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Hesse, G., Matthies, C., Sinzig, W., Uflacker, M. (2019). Adding Value by Combining Business and Sensor Data: An Industry 4.0 Use Case. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds) Database Systems for Advanced Applications. DASFAA 2019. Lecture Notes in Computer Science(), vol 11448. Springer, Cham. https://doi.org/10.1007/978-3-030-18590-9_80
Download citation
DOI: https://doi.org/10.1007/978-3-030-18590-9_80
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-18589-3
Online ISBN: 978-3-030-18590-9
eBook Packages: Computer ScienceComputer Science (R0)