Data Mesh for Managing Complex Big Data Landscapes and Enhancing Decision Making in Organizations

Otmane Azeroual, Radka Nacheva

2023

Abstract

In the age of digitization, data is of the utmost importance. Organizations can gain competitive advantage by being ahead of the curve in organizing data, deriving insights from it, and turning those insights into action. In practice, however, many organizations fail to meet this challenge. Far too many decisions are made without data, decision makers don’t trust their own data. The data warehouse, later the data lake and more recently the data lakehouse have been propagated as solutions to these problems in recent decades. In some cases, this actually succeeds, in other cases challenges remain. The recently prominent data mesh approach changes the perspective on data and in this respect provides valuable impulses for data architectures in general. Data mesh is a new architectural concept for data management in organizations. Therefore, in this paper, we introduce this new data concept and provide a clear overview of the design of a data mesh architecture. We will then show how it can be technically implemented and what potential there is for using data mesh in organizations. Our methodology is a type of investigation that provides a helpful and practical guide to understanding the principles and patterns of data mesh and their implementation in organizations. Our research result has shown that the data mesh approach is therefore a very good tool for organizations where data sharing and reuse is crucial. In addition to facilitating scalability, data mesh can enable better data integration and data management, improving data quality while fostering a culture of data-driven decision-making.

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Paper Citation


in Harvard Style

Azeroual O. and Nacheva R. (2023). Data Mesh for Managing Complex Big Data Landscapes and Enhancing Decision Making in Organizations. In Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS; ISBN 978-989-758-671-2, SciTePress, pages 202-212. DOI: 10.5220/0012195700003598


in Bibtex Style

@conference{kmis23,
author={Otmane Azeroual and Radka Nacheva},
title={Data Mesh for Managing Complex Big Data Landscapes and Enhancing Decision Making in Organizations},
booktitle={Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS},
year={2023},
pages={202-212},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012195700003598},
isbn={978-989-758-671-2},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS
TI - Data Mesh for Managing Complex Big Data Landscapes and Enhancing Decision Making in Organizations
SN - 978-989-758-671-2
AU - Azeroual O.
AU - Nacheva R.
PY - 2023
SP - 202
EP - 212
DO - 10.5220/0012195700003598
PB - SciTePress