Abstract
Emerging networks allow to connect the smart devices and applications efficiently and everywhere, opening a lot of opportunities and use cases for getting and using data. The resulting huge amount of heterogeneous data leads to the new challenges on the data management, like data storage, processing, privacy, lifecycle etc. This work gives and overview of these challenges and the current solutions like cloud computing and data mesh.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Ulema, M.: Big Data and telecommunications telecom analytics. In: Tutorial at International IEEE Conference on BlackSeaCom, Varna, Bulgaria (2016)
Luntovskyy, A., Spillner, J.: Architectural transformations in network services and distributed systems: service vision. Case Studies. Springer Nature, 344 (2017). ISBN: 9–783–6581–484–09
Globa, L., Svetsynska, I., Luntovskyy, A.: Case studies on big data. J. Theoret. Appl. Comput. Sci., JTACS, Polish Acad. Sci. Gdansk (2), 10 (2016). ISSN 2299–2634
Konys, A., Rogoza, W.: Big data and ontologies. In: Talk at ACS International Conference 2016 in Międzyzdroje, p. 3 (October 2016)
Luntovskyy, A., Globa, L., Shubin, B.: From big data to smart data: the most effective approaches for dataaAnalytics. In: Advances in Information and Communication Technology and Systems, pp. 23–40. Springer (2020)
Amazon IoT Device Management and IoT Management (https://aws.amazon.com/iot-analytics)
Google Cloud IoT [https://cloud.google.com/solutions/iot]
Microsoft Azure IoT [https://azure.microsoft.com/en-us/overview/iot/]
SAP IoT [https://www.sap.com/products/iot-data-services.html]
Amazon Machine Learning Services [https://aws.amazon.com/free/machine-learning/]
SAP Document Information Extraction [https://help.sap.com/docs/DOCUMENT_INFORMATION_EXTRACTION]
IBM Watson Smart Document Discovery [https://cloud.ibm.com/docs/discovery?topic=discovery-sdu]
Azure Computer Vision [https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/#overview]
AWS Rekognition [https://aws.amazon.com/rekognition/]
Amazon Lex [https://aws.amazon.com/lex]
Databricks [https://databricks.com/]
SAP Business Technology Platform (BTP [https://www.sap.com/germany/products/business-technology-platform.html]
Delta Lake [https://delta.io/]
Apache Spark [https://spark.apache.org/]
Dehghani, Z.h.: Data Mesh: Delivering Data-Driven Value at Scale. O’Reilly (2022)
Vernon, V.: Implementing Domain-Driven Design. Addison Wesley (2013)
Strengholt, P.: Data Management at Scale. O’Reilly (2020)
Anzo platform [https://cambridgesemantics.com/anzo-platform/]
Ontologies for Industry 4.0 (2019). https://www.cambridge.org/core/journals/knowledge-engineering-review/article/ontologies-for-industry-40/BF86BB5310356D642C82470D67974804
Online demo of SAP Wind Turbines Energy Data Intelligence [https://sapdemostore.com/sap/bc/ui5_ui5/sap/yunifiedstore/index.html#/scenario/16609]
SAP Data Intelligence [https://www.sap.com/products/data-intelligence.html]
Kaiserwetter Looks Ahead with SAP Artificial Intelligence to Support Investors in Renewable Energy. ASUG News and Views (2020) [https://www.asug.com/insights/kaiserwetter-looks-ahead-with-sap-artificial-intelligence-to-support-investors-in-renewable-energy]
SAP Internet of Things [https://www.sap.com/products/intelligent-technologies/iot.html]
SAP Analytics Cloud [https://www.sap.com/products/cloud-analytics.html]
Paolo Collela. Ushering in a better connected future, Ericsson (2017). [https://www.ericsson.com/en/about-us/company-facts/ericsson-worldwide/india/authored-articles/ushering-in-a-better-connected-future]
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Vasyutynskyy, V., Luntovskyy, A. (2023). Data Management in IoT: From Sensor Data to Intelligent Applications. In: Klymash, M., Luntovskyy, A., Beshley, M., Melnyk, I., Schill, A. (eds) Emerging Networking in the Digital Transformation Age. TCSET 2022. Lecture Notes in Electrical Engineering, vol 965. Springer, Cham. https://doi.org/10.1007/978-3-031-24963-1_32
Download citation
DOI: https://doi.org/10.1007/978-3-031-24963-1_32
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-24962-4
Online ISBN: 978-3-031-24963-1
eBook Packages: EngineeringEngineering (R0)