TY - CHAP U1 - Konferenzveröffentlichung A1 - Schüssler, Janik A1 - Karbstein, Denis A1 - Klein, Dennis A1 - Zimmermann, Alfred ED - Zdravkovic, Jelena T1 - Visualizing information for enterprise architecture design decisions using Elastic Stack T2 - BIR-WS 2018 : BIR short papers, workshops and Doctoral Consortium joint proceedings of the BIR 2018 short papers, workshops and Doctoral Consortium, co-located with 17th International Conference Perspectives in Business Informatics Research (BIR 2018) Stockholm, Sweden, September 24-26, 2018. - (CEUR workshop proceedings ; Vol. 2218) N2 - Digital Enterprise Architecture allows multiple viewpoints on a company’s IT landscape. To gain valuable information out of huge amounts of operational data, it is indispensable to have both an understanding of the operations architecture and an engine capable of managing Big Data. The mechanism of understanding huge amounts of data is based on three main steps: collect, process and use. The main idea is focused on extracting valuable information out of Big Data to make better design decisions. The Elastic Stack is an open-source solution to comfortably and quickly handle Big Data scenarios. KW - Big Data analytics KW - Elastic Stack KW - Elasticsearch KW - Logstash KW - Beats KW - Kibana KW - Digital Enterprise Architecture KW - operation architecture KW - operational data KW - log files Y1 - 2018 U6 - https://nbn-resolving.org/urn:nbn:de:bsz:rt2-opus4-20820 UN - https://nbn-resolving.org/urn:nbn:de:bsz:rt2-opus4-20820 UR - http://ceur-ws.org/Vol-2218/ SN - 1613-0073 SS - 1613-0073 SP - 1 EP - 10 S1 - 10 PB - RWTH Aachen CY - Aachen ER -