A Workflow Model for Adaptive Analytics on Big Data

The analysis of Big Data needs to be performed on a range of data stores, both traditional and modern, on data sources that are heterogeneous in their schemas and formats, and on a diversity of query engines. The users that need to perform such data analysis may have several roles, like, business an...

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Bibliographic Details
Main Authors: Kantere, Verena, Filatov, Maxim
Format: Conference Proceeding
Language:English
Subjects:
Adaptation models
adaptive analytics
Adaptive systems
Analytical models
Big data
big data analytics
Data models
Engines
online analytics
Optimization
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Summary:The analysis of Big Data needs to be performed on a range of data stores, both traditional and modern, on data sources that are heterogeneous in their schemas and formats, and on a diversity of query engines. The users that need to perform such data analysis may have several roles, like, business analysts, engineers, end-users etc. Therefore Big Data analytics should be expressed and executed in a manner that is adaptive to the user and the system. We discuss the principles of adaptive analytics and we summarise ongoing work on the creation of a workflow model and, furthermore, a workflow management system that enables the creation and the execution of adaptive analytics. The model focuses on the separation of task dependencies from task functionality and the decoupling of application logic from implementation. Our motivation and applications derive from real use cases of the telecommunication domain.
ISSN:2379-7703
DOI:10.1109/BigDataCongress.2015.106