A STUDY ON OPTIMIZED BIG DATA PERFORMANCE AND ITS INDUSTRIAL DEVELOPMENT
Now a day’s industries are developing fields where big data platform is majorly used. This paper describes the architecture of a cross-sectorial Big Data platform. Storage and processing of data are the main objectives for design and scalable platform. Present environment should be connected with existing platform and use the data gathered to build predictive functions to optimize the production processes. To evaluate the model and development environment is build using this analytical platform with a simulation environment. Different sectors of industries having multiple sites share this same platform. Different domains do Cross-sectorial sharing which enable the transfer of knowledge across. During the development, we adopted a user-centered approach to gather requirements from different stakeholders which were used to design architectural models from different viewpoints, from contextual to deployment. One from the aluminium production and the plastic moulding industry are the two process industry domains which tests the developed architecture.
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