| By: |
Lara Pörtner (G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes, G-SCOP_COSYS - Conception Systémique: Homme, Environnement, Technologies - G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes);
Vivian Klaassen;
Dilara Sezgin;
Ysaline Kievits |
| Abstract: |
In today's rapidly evolving data-driven landscape, the ability to understand,
analyze, and interpret data is more important than ever. With an
everincreasing amount of data being generated and collected at an
unprecedented rate, both individuals and organizations are forced to develop a
high level of data literacy. Data literacy, as the ability to work with,
analyze, understand, use, and argue with data, is therefore the key not to
drown in data. A detailed data literacy assessment can provide companies with
a significant advantage and push their daily and data-related activities to a
mature level. A literature review of existing data literacy frameworks with
their competencies underscore the need for a flexible and adaptable approach
to data literacy that considers the diverse needs and contexts of different
stakeholders. While there is no one-size-fits-all assessment, the frameworks
outlined in this review provide a useful starting point for developing a
common language and set of data literacy skills. The purpose of this paper is
to put an accent on the importance of data literacy by introducing an
assessment of competencies applicable in different industry sectors that can
sustainably support companies to make them realize the need for data literacy
and for leveraging their skills. The competencies as part of a data literacy
framework as a whole will be applied and validated in different industry
sectors for continuous improvement in future research. |
| Keywords: |
Data-Driven Organizations Data Literacy Framework Maturity Assessment Data Management, Data-Driven Organizations, Data Literacy Framework, Maturity Assessment, Data Management |
| Date: |
2024 |
| URL: |
https://d.repec.org/n?u=RePEc:hal:journl:hal-04764249 |