Logo des Repositoriums
 

Software Architecture Best Practices for Enterprise Artificial Intelligence

Kurzanzeige
dc.contributor.authorMartel, Yannick
dc.contributor.authorRoßmann, Arne
dc.contributor.authorSultanow, Eldar
dc.contributor.authorWeiß, Oliver
dc.contributor.authorWissel, Matthias
dc.contributor.authorPelzel, Frank
dc.contributor.authorSeßler, Matthias
dc.contributor.editorReussner, Ralf H.
dc.contributor.editorKoziolek, Anne
dc.contributor.editorHeinrich, Robert
dc.date.accessioned2021-01-27T13:33:27Z
dc.date.available2021-01-27T13:33:27Z
dc.date.issued2021
dc.description.abstractAI systems are increasingly evolving from laboratory experiments in data analysis to increments of productive software products. A professional AI platform must therefore not only function as a laboratory environment but must be designed and procured as a workbench for the development, productive implementation, operation and maintenance of ML models. Subsequently, it needs to integrate within a global software engineering approach. This way, Enterprise Architecture Management (EAM) must implement efficient governance of the development cycle, to enable organization-wide collaboration, to accelerate the go-live and to standardize operations. In this paper we highlight obstacles and show best practices on how architects can integrate data science and AI in their environment. Additionally, we suggest an integrated approach adapting the best practices from both the data science and DevOps.en
dc.identifier.doi10.18420/inf2020_16
dc.identifier.isbn978-3-88579-701-2
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34722
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2020
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-307
dc.subjectSoftware Architecture
dc.subjectEnterprise Architecture
dc.subjectMachine Learning
dc.subjectArtificial Intelligence
dc.subjectMLOps
dc.titleSoftware Architecture Best Practices for Enterprise Artificial Intelligenceen
gi.citation.endPage181
gi.citation.startPage165
gi.conference.date28. September - 2. Oktober 2020
gi.conference.locationKarlsruhe
gi.conference.sessiontitle(Agiles) Enterprise Architecture Management in Forschung und Praxis

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
Name:
C1-4.pdf
Größe:
312.73 KB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

P307 - INFORMATIK 2020 - Back to the Future