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Interconnectivity of Big Data Sources: Exploring Synergistic Relationships among Data

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Title:Interconnectivity of Big Data Sources: Exploring Synergistic Relationships among Data
Authors:Weibl, Johannes
Keywords:Business Intelligence, Business Analytics and Big Data: Innovation, Deployment and Management
Organizational Systems and Technology
Data, Synergy, Informational Complementarity, Systems Theory, Thematic Analysis
Date Issued:08 Jan 2019
Abstract:In recent years, organizations manage an increasing amount of data in order to make better decisions, personalize products, or sell data. By data being combined from various sources, data assets interact with each other. When the interactions are synergistic, they create greater benefits than the sum of the value of the individual data assets. This study explores enablers, mechanisms, and potential outcomes of synergistic interactions among data assets. Based on systems theory and a synthesis of relevant synergy literature, I developed an initial synergy framework in a data context. On this basis, I conducted 14 qualitative interviews to assess the validity of my initial framework. The interview results assisted me in refining and contextualizing a unified conceptual framework of data synergies. The paper reveals that compatibility and contextual relatedness as enablers and informational complementary as a mechanism can lead to super-additive information value among data assets.
Pages/Duration:10 pages
URI/DOI:http://hdl.handle.net/10125/60025
ISBN:978-0-9981331-2-6
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Business Intelligence, Business Analytics and Big Data: Innovation, Deployment and Management


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