Data Mining Report: Re-engineering Business Processes, ISYS301/ITEC601

This data mining report, prepared for the ISYS301/ITEC601 course, examines the Non-Obvious Relationship Awareness (NORA) software and its application in business process re-engineering. The report includes an introduction outlining the alignment of data mining processes for improved functional development, followed by a background section explaining the use of data mining in NORA for information processing and management. Assumptions are made to ensure the completion of the work. As-Is and To-Be process diagrams illustrate the current and proposed data mining workflows. A detailed cost analysis compares the current and proposed processes, highlighting the potential cost savings of the proposed automated approach. The report concludes with a summary of the findings and includes a bibliography of relevant sources. The report is designed to provide insights into data mining techniques and their practical applications, focusing on process improvement and cost optimization.

Running head: DATA MINING REPORT
Data Mining Report
Name of the Student:
Student ID:
Name of the University:

1DATA MINING REPORT
Introduction
The alignment of the data mining process is helpful for managing the utilization of the
improved functional development. The utilization of the functions would be aligned for easing
the functions of using the implication management. The integration would be implied for easing
the listing the implication management for easing the utilization management. The activities
would be implied for easing the alignment development. The usefulness of the operations and
listing of the successful management development can be implied for easing the utilization
management. The formation development is implied for aligning the deployment and formation.
The Non-Obvious Relationship Awareness (NORA) would be aligned for easing the implication
and development of formation management. The implication management would be effectively
formed using the cohesive management.
Background
The comprehensive use of the development model can be assisted by the significant
alignment model. The data mining in NORA is helpful for successfully forming the use of data
collectively and easing the flow of information processing. The use of the successfully implied
management process can be effectively used for easing the significance of developing faster and
effective management process. The usefulness of the data mining can be aligned cohesively for
easing the implication management. The alignment would be implied for managing the
successful alignment model. The new process would involve the implication of the activities of
data mining using innovative technology.

2DATA MINING REPORT
Assumptions
Some assumptions have to be made for ensuring the completion of the work and
alignment of the improved communication management. The alignment would also take care of
the information management of the data mining process. The automation of the data mining
would include the development of the operations for aligning the inclusion of the effective data
collection and mining process.

3DATA MINING REPORT
As-Is Process Diagram
The following is the As-Is diagram for the data mining of NORA,
The diagram has been developed for the existing functionalities of the operations and alignment of the improved functional analysis model. The influence of the functions has bene helpful for defining the simplification of the functions to manual
process of data generation, business understanding, data publishing, data preparation, modelling, report and decision making. The complete data collection and mining process is supported by the use of these processes.
To-Be Process Diagram
The following is the to-be diagram for the data mining of the NORA,

4DATA MINING REPORT

5DATA MINING REPORT
The proposed method of data mining would be supported by the utilization of the automatic process. NORA would get the benefit of easy work process and aligning it with the completion of the successful project completion. The implication of
the improved management would be achieved by the use of the processes of data generation, business understanding, data preparation process apply PPDP, data publishing, data preparation, data privacy preserving process, modelling, report, legal
measure, get report, evaluation/validating the results, and report and decision making. The ease of dividing the work into phases of data collection and data mining is helpful for achievement of the successful completion of the data modelling.
Cost Analysis
Task
Document Type Process Time (Elapsed) Process Time (Working) Rate Cost
Current Proposed Current Proposed Current Propose
d Current Proposed Current Proposed
Data generation Manual Automatic 30 15 200 100 $15.00 $10.00 $3,450.00 $1,150.00
Business Understanding Manual Automatic 10 5 50 20 $10.00 $15.00 $600.00 $375.00
Data Preparation Process Apply
PPDP NA Automatic 0 10 0 50 $0.00 $10.00 $0.00 $600.00
Data Publishing Manual Automatic 15 10 100 50 $20.00 $20.00 $2,300.00 $1,200.00
Data Preparation Manual Automatic 50 10 350 50 $15.00 $10.00 $6,000.00 $600.00
Data Privacy Preserving Process NA Automatic 0 20 0 100 $0.00 $15.00 $0.00 $1,800.00
Modeling Manual Automatic 20 12 200 60 $15.00 $10.00 $3,300.00 $720.00
Report Manual Automatic 10 7 100 20 $20.00 $20.00 $2,200.00 $540.00
Legal Measure NA Automatic 0 4 0 10 $0.00 $10.00 $0.00 $140.00
Get Report NA Automatic 0 5 0 30 $0.00 $15.00 $0.00 $525.00
Evaluation/Validating the Results NA Automatic 0 6 0 40 $0.00 $10.00 $0.00 $460.00
Report and Decision Making Manual Automatic 25 6 240 60 $25.00 $20.00 $6,625.00 $1,320.00
Total $24,475.00 $9,430.00

6DATA MINING REPORT
Conclusions
The alignment of the data mining process was helpful for managing the utilization of the
improved functional development. The utilization of the functions had been aligned for easing
the functions of using the implication management. The integration had been implied for easing
the listing the implication management for easing the utilization management. The activities had
been implied for easing the alignment development. The usefulness of the operations and listing
of the successful management development was implied for easing the utilization management.
The formation development was implied for aligning the deployment and formation. The Non-
Obvious Relationship Awareness (NORA) had been aligned for easing the implication and
development of formation management. The implication management had been effectively
formed using the cohesive management.

7DATA MINING REPORT
Bibliography
Chen, D and Zhao, H., 2012, March, “Data security and privacy protection issues in cloud
computing”, in Computer Science and Electronics Engineering (ICCSEE), 2012
International Conference on (Vol.1, pp. 647-651).
Chen, H.; Chiang, R. and Storey, V. 2012. "Business Intelligence and Analytics: From Big Data
to Big Impact," MIS Quarterly, 36(4) pp.1165-1188.
Cormode, G., Procopiuc, C, Srivastava, D., Shen, E., Yu, T., 2013, "Empirical privacy and
empirical utility of anonymized data", IEEE 29th International Conference on Data
Engineering Workshops (ICDEW), pp. 77-82.
Lyon, D 2014, “Surveillance, Snowden, and big data: Capacities, consequences, critique”, Big
Data & Society, 1(2), pp.1-13.
Magdy, W., Darwish, K., and Weber, I. (2015), “# FailedRevolutions: Using Twitter to study the
antecedents of ISIS support”, arXiv preprint arXiv:1503.02401
Inthasone S., Pasquier N., Tettamanzi A., da Costa Pereira C. (2014) “The BioKET Biodiversity
Data Warehouse: Data and Knowledge Integration and Extraction” In: Blockeel H., van
Leeuwen M., Vinciotti V. (eds) Advances in Intelligent Data Analysis XIII. IDA 2014.
Lecture Notes in Computer Science, vol 8819. Springer.
Stein, S., Hamilton, B., Peterson, T., Guyer, C., 2016, Develop using Always Encrypted
with .NETFramework Data Provider. [Online] Available at:

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Xu, L., Jiang, C., Wang, J., Yuan, J., and Ren, Y., 2014, “Information Security in Big Data:
Privacy and Data Mining”, IEEE Access, vol. 2, pp.1149-1176.