Start Date
10-12-2017 12:00 AM
Description
Firms are attempting to more effectively exploit big data gathered from different sources to increase data diagnosticity. However, with the huge volume of generated data, the large variety of heterogeneous data, and the fast velocity of arriving data, the quality of data is far from perfect which may decrease data diagnosticity within firms. This research-in-progress study draws on the Active Learning Theory, Information Retrieval Interaction Model, and Wang and Strong’s data quality framework to investigate the impact of bigness of data on firm data diagnosticity and explore the mediating role of data quality. The results will be achieved using a combination of qualitative and quantitative methods. Potential contributions to theory and practice are also discussed.
Recommended Citation
Ghasemaghaei, Maryam, "The Impact of Big Data on Firm Data Diagnosticity: Mediating Role of Data Quality" (2017). ICIS 2017 Proceedings. 2.
https://aisel.aisnet.org/icis2017/DataScience/Presentations/2
The Impact of Big Data on Firm Data Diagnosticity: Mediating Role of Data Quality
Firms are attempting to more effectively exploit big data gathered from different sources to increase data diagnosticity. However, with the huge volume of generated data, the large variety of heterogeneous data, and the fast velocity of arriving data, the quality of data is far from perfect which may decrease data diagnosticity within firms. This research-in-progress study draws on the Active Learning Theory, Information Retrieval Interaction Model, and Wang and Strong’s data quality framework to investigate the impact of bigness of data on firm data diagnosticity and explore the mediating role of data quality. The results will be achieved using a combination of qualitative and quantitative methods. Potential contributions to theory and practice are also discussed.