Convergence-Directed, Semantic Model for Integrating Large-Scale, Dynamic, and Heterogeneous Databases
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Date
2017-01-01
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Department
Information Systems
Program
Information Systems
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This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu
Distribution Rights granted to UMBC by the author.
Distribution Rights granted to UMBC by the author.
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Abstract
Data abounds today. The ability to properly employ large amounts of data for business decisions and opportunities is critical to business success. Rarely does a single data source or database prove sufficient for a dynamic, unfolding business action. Business decision-making requires integrating data quickly and efficiently. However, the inherent differences between databases make it both time-consuming and costly to achieve a useful integration. More importantly, the storage of much of today'sdata has migrated away from the traditional, relational database technology and switched to NoSQL database technology. The latter provides a new set of challenges for data integration. To address the above challenges, the semantic integration model offers a path to simplify integration across different NoSQL databases. It achieves this through an iterative, incremental integration that directly involves the non-technical business user ? the key to exploiting the business opportunity. The model contrasts current integration methods and is evaluated against a prototype that implements and tests the model with appropriate data participants. The model demonstrates an easier method to quickly review potential data integration candidates, integrate selected candidates, and maintain the alignment of the data integration with the evolving NoSQL technologies and the business opportunity itself.