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ThinkMind // DATA ANALYTICS 2021, The Tenth International Conference on Data Analytics // View article data_analytics_2021_3_50_60037
Discovering DataOps: A Comprehensive Review of Definitions, Use Cases, and Tools
 Authors: Kiran Mainali Lisa Ehrlinger Johannes Himmelbauer Mihhail Matskin Keywords: DataOps; Data lifecycle management; Data analytics. Abstract: Data management approaches have changed drastically in the past few years due to improved data availability and increasing interest in data analysis (e.g., artificial intelligence). The volume, velocity, and variety of data requires novel and automated ways to "operate" this data. In accordance with software development, where DevOps is the de-facto standard to operate code, DataOps is an emerging approach advocated by practitioners to tackle data management challenges for analytics. In this paper, we uncover DataOps from the scientific perspective with a rigorous review of research and tools. As a result, we make the following three-fold contribution: we (1) outline definitions of DataOps and their ambiguities, (2) identify the extent to which DataOps covers different stages of the data lifecycle, and (3) provide a comprehensive overview on tools and their suitability for different stages of DataOps. Pages: 61 to 69 Copyright: Copyright (c) IARIA, 2021 Publication date: October 3, 2021 Published in: conference ISSN: 2308-4464 ISBN: 978-1-61208-891-4 Location: Barcelona, Spain Dates: from October 3, 2021 to October 7, 2021
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