Building a general concept of analytical services for analysis of structured data

Atheer Hadi Al-Rammahi, Mohammed Hamzah Abed, Mustafa Jawad Radif

Abstract


In this paper, “Building a common concept of analytical services for analyzing structured data” was proposed to build an analytical service to provide forecasts, descriptive and comparative data summaries using modern Microsoft technologies. This service will allow users to perform flexible viewing of information, receive arbitrary data slices and perform analytical operations of drill-down, convolution, pass-through distribution, the comparison in time. With the help of data mining, it is possible to detect previously unknown, non-trivial, practically useful and accessible interpretations of knowledge that are necessary for the organization's decision-making. Also, each client can interact with the service and thus monitor the displayed analytical information. In the process of work the following tasks were solved: investigated the subject area; studied materials relating to systems and technologies for their implementation; designed service architecture and applications to configure the service; selected technologies and tools for the implementation of the system; implemented the main frame of the system; modules for interaction with analysis services, data mining (a priori algorithm) and partially a module of neural networks; a report was written and a presentation of the results was prepared; The developed service will be useful to all organizations that are interested in obtaining analytical reports and other previously unknown information on their accumulated data. For example, organizations can analyze the impact of advertising, customer segmentation, search for signs of profitable customers, analyze product preferences, forecast sales volumes, and more.

Keywords


ANALYSIS OF STRUCTURED DATA, OLAP, Physical Data Model, Database Scheme, Olap-cubes

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DOI: http://dx.doi.org/10.21533/pen.v7i3.658

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Copyright (c) 2019 Atheer Hadi Al-Rammahi

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This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN: 2303-4521

Digital Object Identifier DOI: 10.21533/pen

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License