DATA INTEGRATION MODEL FOR FASTER DATA EXTRACTION AND RETRIEVAL FROM SEMI-STRUCTURED DATA FORMAT
Collections of data is crucial across a wide variety of field because of increasing data rapidly year by year. These collections are important for many organizations to make a correct decision using business intelligent applications. A business intelligent application must have capability to coll...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
UNIVERSITI MALAYSIA TERENGGANU
2022
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| Online Access: | http://umt-ir.umt.edu.my:8080/handle/123456789/15638 |
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| Summary: | Collections of data is crucial across a wide variety of field because of increasing data
rapidly year by year. These collections are important for many organizations to make
a correct decision using business intelligent applications. A business intelligent
application must have capability to collect and integrate all data from different data
sources. One of the challenges in development of business intelligent application is
data integration. This challenge is happened because of data structure are different.
This research is looking for suitable data integration model in order to allows data
integration from different data sources. Native XML (NXD) is one the model has been
used in data integration. In this model, elements and attributes for each data are extract
and store into Relational Database Management System (RDBMS). Meanwhile, the
value for each element and attribute are stored in XML format. Based on the
experiments has been done by previous researchers, NXD can produce a better
performance during data insertion response time and query processing response time
using SigmodRecord and DBLP datasets. However, the efficiency of NXD still has
room for improvement. In the initial experiment, list of special character can be
removed to improve the performance of NXD has been idenfitied in the SigmodRecord
and DBLP datasets. |
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