International Journal of Advances in Engineering & Technology, Jan. 2014. ©IJAET ISSN: 22311963 2739 Vol. 6, Issue 6, pp. 2739-2744 HEURISTIC APPROACH FOR CUSTOMER DATA INTEGRATION Seema Lute 1 and Prakash R Devale 2 1 Scholor and 2 Professor & Head, Department of Information technology, Bharati Vidyapeeth Deemed University, Pune, India ABSTRACT In today’s world maintaining users or customers data by giant industries like telecom, Insurance etc. is a very cumbersome task and more over allowing some different domain to access this data is even a hard task than the prior one. So integrating these data on common platform so that it can be shared by the different data requesters and provider is a quite an appreciation task. However, maintaining and integrating quality customer data is one of the greatest challenges it executives face—and this challenge only gets more daunting as businesses both grow and become more complex. Economic slowdown has fuelled customer data integration (CDI) of different enterprises under a single roof. Today, more or less all enterprises have CDI solution, which interacts closely with the ERP, CRM systems. Hence CDI is very critical and will act as catalyst to ERP, CRM system integrations to a large extent. Success in CDI will also ensure reduced impact on customer –the top most priority during the integration. In our approach of CDI batched stream processing (BSP) is incorporated, where it is a distributed data processing paradigm that models recurring batch computations on incrementally bulk-appended data streams. The model is inspired by our empirical study on a trace from a large-scale production data-processing cluster at the web server end; it allows a set of effective query optimizations that are not possible in a traditional integration model. And also selective encryption model to preserve the privacy of the customer data makes the system more effective and enriched. K EYWORDS: Customer Data Integration (CDI), Batch Stream Processing (BSP), Selective Encryption. Privacy Preserving. I. INTRODUCTION As yet, there is no universal set of CDI standards. Today’s CDI standards are a function of individual organizational needs. CDI may be characterized as “the combination of processes, controls, automation and skills necessary to standardize and integrate customer data originating from different sources.” And “a comprehensive set of technology components, services, and business processes that create, maintain, and make available an accurate, timely, integrated and complete view of a customer across lines of business, channels, and business partners.” CDI is technically a subset of MDM (Master Data Management) which comprises a set of processes and tools which consistently define and manage the non-transactional data entities of an organization. CDI and MDM however share a common logical approach. Both integrate data from across different sources. Both document data lineage and data evolution over time. Both strive to achieve single “golden” records which consolidate data and eliminate duplication of information. MDM is often perceived as covering a broader spectrum of data. However, in reality, although initially focused on customer data, CDI solutions can cover much of the same ground. The essential construct is the same—a truly robust CDI solution can be readily expanded to include larger MDM applications by moving beyond customer data to include that of other key parties.