Design of Data Acquisition Process and Its Validation Through Statistical Approaches
D. NagaMalleswari1, K. Subrahmanyam2
1D. Naga Malleswari, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, India.
2Dr. K. Subrahmanyam, Department of Computer Science Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur, India.
Manuscript received on 05 April 2019 | Revised Manuscript received on 10 May 2019 | Manuscript published on 30 May 2019 | PP: 3242-3245 | Volume-8 Issue-1, May 2019 | Retrieval Number: A1845058119/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In SIS framework proposed, data acquisition is playing a vital role. It is acquired for source code analysis, information acquirement, and SWOT processes involved. This paper presents basic factors used in data acquisition process for all the three processes. The obtained data is validated through KMO test, Cronbach al pha test, and KS test for verifying its reliability, normality and validity. The values of data have proven that it has passed KMO test, α test, and normality test. This validated data is further used in SIS Framework.
Index Terms: Cronbach Alpha Test, Data Acquisition Process, Information Acquirement, KMO Test, KS Test, SIS Framework,
SWOT.
Scope of the Article: Big Data Quality Validation