A Conceptual Framework for Big Data Models Using Filtration Theory

摘要

Big data and data analytics are becoming norm of the society. In the digital age, abundance of untapped structuredand unstructured data is generated that need to be mined. This data may contain useful information that is still unexplored.Data are generated as soon as we step out of the house. This data is generated via social networking, sensors, mobiles, appsand many smart devices. The speed, variety and volume with which this data is generated is making current thinkingobsolete. Both the private and the public sectors are thinking new ways of analyzing and using data for competitiveadvantage, e-services, e-information etc. -- big data analytics is an outgrowth of this thinking. Though private sector hasachieved great success public sector is not far behind. Researchers have used statistical and optimization analytical techniqueto study various issues, however, visual analytical applications are still in their infancy. This may be due to separate streamsof visualization and analytics research. Lately, both streams are being combined to create data-driven analysis using visualanalytics. This paper uses filtration theory in developing a model and uses visual analytics, to study crime statistics in ametropolitan area.