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) |
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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 |
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Country | 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