Data Analytics and Business Intelligence Project: Verification

This project focuses on verifying document and facial similarity data using Excel. It involves analyzing data from document checks and face similarity reports to validate the authenticity of IDs. The process includes creating pivot tables to calculate totals and generate charts, facilitating data validation for specific dates and comparing facial features with submitted IDs. The project also touches upon the use of Veritas software for data analysis from Oracle and its authorized licenses. The final outcome successfully demonstrates the verification process, utilizing Excel for pivot tables, chart creation, and data validation to ensure the reliability of document and facial similarity checks. The project includes references to various research papers related to data analysis and business intelligence.

Data Analytics and
Business Intelligence

Table of Contents
Introduction.........................................................................................................................................1
Facial Similarity Check.......................................................................................................................2
Document Checks................................................................................................................................4
Veritas..................................................................................................................................................5
Conclusion............................................................................................................................................5
References............................................................................................................................................6

Introduction
In this project we have to verify the document and facial similarity check using excel.
We have used document check and face similarity check data for analysing data using excel
sheet. First step is to create the pivot table for analysing the data. To verify the document and
facial check data for data validation. Select the particular data for validating on the excel
sheet. In the document, report the data for verifying the photo ID is valid or not. The facial
report data is to be verified with the face in the picture as the same with that on the submitted
ID on excel spreadsheet.
Facial Similarity Check
In this data contains the user id,result,face comparison result, created date and time,
facial image integrity results, visual authenticity results and attempt id (O’Neill, 2011).We
have to compare all these data and create a chart for the grand total. To calculate the clear
total, consider total, blank total and grant total for facial reports data. To validate the data for
particular date and verify that submitted ID also.
Select the particular date for validation and enter the maximum and minimum sum of the
data. Select the value and enter “OK’ for data validation. The next step is to create the pivot
table and analyse the data.

It calculates the clear total, blank total and grant total for the report and then creates the chart
for that data.
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0
50000
100000
150000
200000
250000
300000
350000
400000
clear - clear - clear - clear
clear - clear - clear - consider
clear - clear - clear - (blank)
clear - consider - consider - clear
clear - consider - consider - consider
clear - consider - consider - (blank)
consider - (blank) - consider - clear
consider - (blank) - consider - consider
consider - (blank) - consider - (blank)
(blank) - (blank) - consider - clear
(blank) - (blank) - consider - consider
(blank) - (blank) - consider - (blank)
It displays the ID and thisIDis grant total for all facial reports.The candidate identifies facial
integrity result for decreasing in the clear rate. The facial rate is decreasing compared to other
results.

Document Checks
The document reports contains user id,result, visual authenticity result,image integrity
result,face detection result, image quality result, created date and time, supported document
result, data validation results,data consistency result and sub result. We have to validate the
data and check if the photo ID is valid or not (Ginet, 2010).
Select the particular data for validating purpose and check the data is valid or not. Then
create the pivot table for calculating the clear total, grant total and blank total then create the
chart for that table (Doomen, 2012).
Create the chart for clear total value, grant total value and blank total value.

Veritas
This software is used for binary form from Oracle or its authorized licences that
includes machine readable material and updates or error corrections provided by Oracle. It is
used for proposals, representations and warranties for quote, order and acknowledgement. It
contains the source code for parse the data and analysis the data. In this software,we are using
the analysis of the data for the document and face reports (Colubi and Denoeux, 2014).
Total Rate Pass Fail
0
1000
2000
3000
4000
5000
6000
7000
Chart Title
Figure 1: Facial Report

1
0
1000
2000
3000
4000
5000
6000
7000
Chart Title
Pass Rate Pass Fail
Figure 2: Document Report
Figure 3: Root Cause Analysis
Conclusion
This project has successfully been used to verify the ID and data for document reports
and facial similarity reports using excel spreadsheet. First step was to create the pivot table
for analysing the data. Then, to verify the document and the facial check data for data

validation. Select the particular data for validating on the excel sheet. The document report is
used for verifying the ID and facial report data and to verify that the face in the picture is the
same as per the submitted ID on the excel spreadsheet. We have used the excel sheet for
creating the pivot table and chart for both the repots. The pivot table contains the blank total,
grant total and that values are used to create the chart .Finally, the document and face report
verification has been successfully completed and the solution is sensible.
References
Colubi, A. and Denoeux, T. (2014). Special issue on imprecision in statistical data
analysis. Computational Statistics & Data Analysis, 71, pp.787-788.
Doomen, J. (2012). Conceitualizando significado. Veritas (Porto Alegre), 57(2), p.84.
Ginet, C. (2010). Réplica a Hetherington. Veritas (Porto Alegre), 55(2).
O’Neill, D. (2011). Business Intelligence Competency Centers. International Journal of
Business Intelligence Research, 2(3), pp.21-35.