ABSTRACT
The SDA workshop at WSDM 2015 is the fifth International Workshop on Scalable Data Analytics, following the previous four workshops of SDA respectively held at IEEE Big Data 2013, PAKDD 2014, IEEE Big Data 2014, and IEEE ICDM 2014. This series of workshops aims to provide professionals, researchers, and technologists with a single forum where they can discuss and share the state-of-the-art theories and applications of scalable data analytics technologies. In particular, in the era of information explosion, the scientific, biomedical, and engineering research communities are undergoing a profound transformation where discoveries and innovations increasingly rely on massive amounts of data. The characteristics of volume, velocity, variety and veracity originated in the massive big data then bring challenges to current data analytics techniques. The focus of the fifth SDA is to discuss how we can scale up data analytics techniques for modeling and analyzing big data from various domains.
Index Terms
- WSDM'15 Workshop Summary / Scalable Data Analytics: Theory and Applications
Recommendations
Experience-based analytics
CASCON '15: Proceedings of the 25th Annual International Conference on Computer Science and Software EngineeringData has been called the new oil. Despite of its high value, only one percent of the world's data has been extracted for its insights. Data analytics is currently available only to the technical elite of data and IT experts, completely out of reach for ...
Perspectives, Motivations and Implications Of Big Data Analytics
ICARCSET '15: Proceedings of the 2015 International Conference on Advanced Research in Computer Science Engineering & Technology (ICARCSET 2015)As today there is an enormous volume of data, examining these large sets contains structure and unstructured data of different types and sizes; big data analytics is used. Data Analytics allows the user to analyze the unusable data to make a faster and ...
Big data software analytics with Apache Spark
ICSE '18: Proceedings of the 40th International Conference on Software Engineering: Companion ProceeedingsAt the beginning of every research effort, researchers in empirical software engineering have to go through the processes of extracting data from raw data sources and transforming them to what their tools expect as inputs. This step is time consuming ...
Comments