Abstract
The increased reliance on data driven enterprise has seen an unprecedented investment in big data initiatives. Organizations averaged US$8M in investments in big data-related initiatives and programs in 2014, with 70% of large enterprises and 56% of small and medium enterprises (SMEs) having already deployed, or planning to deploy, big-data projects [1]. As companies intensify their efforts to get value from big data, the growth in the amount of data being managed continues at an exponential rate, leaving organizations with a massive footprint of unexplored, unfamiliar datasets. On February 8th, 2015, a group of global thought leaders from the database research community outlined the grand challenges in getting value from big data [2]. The key message was the need to develop the capacity to 'understand how the quality of data affects the quality of the insight we derive from it'.
| Original language | English (US) |
|---|---|
| Title of host publication | 2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1446-1447 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781509020195 |
| DOIs | |
| State | Published - Jun 22 2016 |
| Event | 32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland Duration: May 16 2016 → May 20 2016 |
Other
| Other | 32nd IEEE International Conference on Data Engineering, ICDE 2016 |
|---|---|
| Country/Territory | Finland |
| City | Helsinki |
| Period | 5/16/16 → 5/20/16 |
ASJC Scopus subject areas
- Artificial Intelligence
- Computational Theory and Mathematics
- Computer Graphics and Computer-Aided Design
- Computer Networks and Communications
- Information Systems
- Information Systems and Management