Transforming Big Data into Smart Data: Deriving Value via Harnessing Volume, Variety, and Velocity using Semantic Techniques and Technologies
Big Data has captured a lot of interest in industry, with anticipation of better decisions, efficient organizations, and many new jobs. Much of the emphasis is on the challenges of the four V's of Big Data: Volume, Variety, Velocity, and Veracity, and technologies that handle volume, including storage and computational techniques to support analysis (Hadoop, NoSQL, MapReduce, etc). However, the most important feature of Big Data, the raison d'etre, is none of these 4 V's — but value. In this talk, I will forward the concept of Smart Data that is realized by extracting value from a variety of data, and how Smart Data for growing variety (e.g., social, sensor/IoT, health care) of Big Data enable a much larger class of applications that can benefit not just large companies but each individual. This requires organized ways to harness and overcome the four V-challenges. In particular, we will need to utilize metadata, employ semantics and intelligent processing, and go beyond traditional reliance on ML and NLP.
Digital Object Identifier (DOI)
2014 IEEE 30th International Conference on Data Engineering, 2014.
© IEEE, 2014
Sheth, A. P. (2014). Transforming Big Data into Smart Data: Deriving Value via Harnessing Volume, Variety, and Velocity using Semantic Techniques and Technologies. IEEE 30th International Conference on Data Engineering.