pisco_log
banner

Conceptual Model of Data Ecosystem for Non-Tech Small Organizations

Han Sun

Abstract


Using data effectively is crucial for success in the current business world. Small non-tech organizations struggle with this due to
limited resources, different systems, and constantly changing technology. To address these challenges, this study proposes a conceptual framework for designing a flexible and reusable data ecosystem, tailored specifically for small non-tech organizations. It also outlines the feedback
loops that drive continuous improvement and innovation within the data ecosystem. Key considerations include data source integration, data
quality management, and analytics capabilities. The proposed framework offers small non-tech organizations a structured approach to managing data assets effectively, enabling them to make informed decisions, optimize processes, and drive innovation.

Keywords


Data Ecosystem; Small Non-tech Organizations; Data Life-circle

Full Text:

PDF

Included Database


References


[1] Mayhew H, Saleh T, Williams S (2016) Making data analytics work for youinstead of the other way around. McKinsey Q Oct 4, pp 2941

[2] Loebbecke C, Picot A (2015) Reflections on societal and business model transformation arising from digitization and big data analytics:

a research agenda. J Strateg Inf Syst 24(3):149157

[3] Riasanow, 2021: Core, intertwined, and ecosystem-specific clusters in platform ecosystems: analyzing similarities in the digital transformation of the automotive, blockchain, financial, insurance and IIoT industry, Electronic Markets, 31, 1, 89-104

[4] McAfee, Andrew 2012: Big Data: The Management Revolution

[5] Tobias Riasanow, 2017, DIGITAL TRANSFORMATION IN THE AUTOMOTIVE INDUSTRY: TOWARDS A GENERIC VALUE NETWORK

[6] Andreas Hein, 2020, Digital platform ecosystems, Electron Markets, 30, 1, 87, 98

[7] 2015 Service innovation: A servicedominant logic perspective. MIS Quarterly, 39(1), 155175.

[8] Tsujimoto et al. 2017, Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies

[9] Kogalovsky, 2009: Conceptual and ontological modeling in information systems, Programming and Computer Software, 35, 5, 241-256

[10] Robinson, 2010: Conceptual modelling: Who needs it. SCS M&S Magazine, 2, 17.

[11] Yiming Lin, Hongzhi Wang, Jianzhong Li, Hong Gao 2019: Data source selection for information integration in big data era, Information Sciences, 479, 197-213




DOI: http://dx.doi.org/10.18686/frim.v2i4.4353

Refbacks

  • There are currently no refbacks.