Abstract
Business data has been one of the current and future research frontiers, with such big data characteristics as high-volume, high-velocity, high-privacy, and so forth. Most corporations view their business data as a valuable asset and make efforts on the development and optimal utilization on these data. Unfortunately, data management technology at present has been lagging behind the requirements of business big data era. Based on previous business process knowledge, a lifecycle of business data is modeled to achieve consistent description between the data and processes. On this basis, a business data partition method based on user interest is proposed which aims to get minimum number of interferential tuples. Then, to balance data privacy and data transmission cost, our strategy is to explore techniques to execute SQL queries over encrypted business data, split the computations of queries across the server and the client, and optimize the queries with syntax tree. Finally, an instance is provided to verify the usefulness and availability of the proposed method.
Highlights
With the advent of Big Data, attentions from all walks of life gradually focus on exploiting their controllable data so as to realize a satisfactory profit
In enterprise-led dataspace, business process data is the key element in data modeling, which has such characteristics as large-volume, strong temporal correlation and stable lifecycle
Artifacts describe the business-relevant data and their lifecycles which is an important property of business data and describes the whole dynamic process of business data
Summary
With the advent of Big Data, attentions from all walks of life gradually focus on exploiting their controllable data so as to realize a satisfactory profit. In enterprise-led dataspace, business process data is the key element in data modeling, which has such characteristics as large-volume, strong temporal correlation and stable lifecycle. These characteristics make it an extreme challenge for current query schemes. Artifact-centric approach [11] is the representative method in data-centric business process management and has been applied in various client engagements, including financial [12], supply chain, retailer [13], bank, pharmaceutical research [14], and cooperative work [15].
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