W7- Case Study question From Pages 589-591 and 630-631

Note: – Must require——–

APA format (Times New Roman, size 12 and 2 space)

MS Visio diagram OR MS Word Smart Art

Minimum 3 or more References including Sharda mentioned below.

W7: Case Studies – Graded Case Study Assignment (Pages 589-591 and 630-631)

Graded Assignment:  Case Studies – (Follow all steps below)

Carefully review and read both case studies found in your textbook from Pages 589-591 and 630-631

Sharda, R., Delen, D., & Turban, E. (2015) Business intelligence and analytics: Systems for decision support (10th ed.). Boston: Pearson.

Digital: ISBN-13: 978-0-13-340193-6 or Print: ISBN-13: 978-0-13-305090-5

After reading and analyzing both studies, address all case study questions found within the case studies in scholarly detail prepared in a professionally formatted APA paper.

When concluding the paper, expand your analytical and critical thinking skills to develop ideas as a process or operation of steps visually represented in a flow diagram or any other type of created illustration to support your idea which can be used as a proposal to the entity or organization in the cases to correct or improve any case related issues addressed.  This is required for both cases.

When developing illustrations to support a process or operation of steps, Microsoft Word has a tool known as “Smart Art” which is ideal for the development of these types of illustrations or diagrams.  To get acquainted with this tool, everyone can visit www.youtube.com using a keyword search “Microsoft Word Smart Art Tutorials” to find many video demonstrations in using this tool.

Minimum Paper Expectations

· Page Requirements:  The overall paper supporting both cases will include a minimum of “4” pages of written content.

· Research Requirements:  The overall paper will be supported with a minimum of “3” academic sources of research and one of the sources can be the textbook.

· Application Technology:  Microsoft Word will be used to prepare this paper.

· Professional Format: APA will be used to prepare the professional layout and documentation of research.

· Important Note:  Do not fall below minimum page and research requirements.

======

Questions from the text Book which we need to elaborate in our case study

QUESTIONS FOR THE END-OF-CHAPTER APPLICATION CASE (Page 589- 591)

INTRODUCTION —

1. How big is Big Data for Discovery Health?

2. What big data sources did Discovery Health use for their analytic solutions?

3. What were the main data/ analytics challenges Discovery Health was facing?

4. What were the main solutions they have produced?

5. What were the initial results/benefits? What do you think will be the future of Big Data analytics at Discovery?

Diagram flow – MS word ART or MS Visio etc… (This is must)

QUESTIONS FOR THE END-OF-CHAPTER APPLICATION CASE (Page 630-631)

INTRODUCTION —-

1. What is main business problem faced by Southern States Cooperative?

2. How was predictive analytics applied in the application case?

3. What problems were solved by the optimization techniques employed by Southern States Cooperative?

Diagram flow – MS word ART or MS Visio etc… (This is must)

CONCLUSION

<xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx>

Reference info. Minimum 3 or more.

TEXT BOOK Attached.

PLACE YOUR ORDER NOW

Table of Contents

Introduction. 3

Application case – Tax Collections Optimization for New York State. 3

1. What is the key difference between the former tax collection system and the new system? 3
2. List at least three benefits that were derived from implementing the new system. 3
3. In what ways do analytics and optimization support the generation of an efficient tax collection system? 4
4. Why was tax collection a target for decreasing the budget deficit in the State of New York? 4

Diagram1. 5

Application case – Solving Crimes by Sharing Digital Forensic Knowledge. 6

1. Why should digital forensics information be shared among law enforcement communities? 6
2. What does egocentric theory suggest about knowledge sharing?. 6
3. What behavior did the developers of NRDFI observe in terms of use of the system?. 7
4. What additional features might enhance the use and value of such a KMS?. 7

Conclusion. 8

Diagram2. 8

 

 

 

Introduction

There are several difference amid the previous former tax collection and the new tax system. The state incorporated new system that also brought about some several changes on budget deficit and tax collection system. The new system also created more effective and efficient policies and rules on tax collection reducing the need of too many personnel. This paper discusses about both the old system and the new system.

Application case – Tax Collections Optimization for New York State

1. What is the key difference between the former tax collection system and the new system?

First and foremost, difference in that the previous tax system has rigid rules that took a long time to adopt since it needed too much resources while the new system had simple rules that took a short time to implement. Secondly the previous tax system emphasized on what could be done while the new system focus on what should be done by the tax collection officers. Previously the tax collection system employed the linear approach method for the identification and collection of delinquent taxes while the new system incorporated smarter decision on which of the delinquent cases to focus on first within the available framework. The new system was much different from the old system since it utilized the C-RL methodology to set up rules for tax collection while the old one did not incorporate any methodology when setting up new rules.

2.  List at least three benefits that were derived from implementing the new system.

Implementing the new system brought about several advantages. To begin with, the new system that was adopted in the year 2009 allowed the tax collection agency to only gather the delinquent tax whenever it was needed. Second benefit for implementing the new tax system was the fact that there was evident year to year rise in revenue collected from 2007 to 2010 that summed up to 83 million. Anthe third benefit was the fact that there was a 7 percent rise I revenue in the year 2009 and the year 2010 which was as a result of adoption of third new system which increased the revenue collected to support the state programs.

3. In what ways do analytics and optimization support the generation of an efficient tax collection system?

Optimization and analytics supported the effective generation of tax collection system in diverse ways. First the optimization and analytic process were grouped with the Constrained Reinforcement Learning (C-RL) strategy. This strategy assisted the development of the rule for the tax collection founded on the taxpayer features (She, 2017). With this they identified that the previous behavior of the taxpayer was one of the major cause predictor of the taxpayer expected future character, and this realization was leveraged by the methodology utilized. Primary, the data analytics and the future optimization procedure were created founded on inputs such as a list of the businesses rules on the collection of taxes, resources available and the condition of tax collection procedures (Sharda, Delen, & Turban, 2015).

 4. Why was tax collection a target for decreasing the budget deficit in the State of New York?

The reason as to why the tax collection was declining the budget deficit in the State of New York was partly because of the unfavorable state economic conditions before the year 2009. The main part of the state’s budget is the revenue from the tax collection that create around forty percent of the states’ yearly revenue. The tax collection method seemed as the key area that facilitated the reduction of the states’ budget deficit if advanced (Mahalakshmi et al., 2019).

 

 

 

Diagram1

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Application case – Solving Crimes by Sharing Digital Forensic Knowledge.

The quality of digital instruments which might be explored using the forensic analysis is overwhelming incorporating things from the home computers direct to the video games console to an engineering module getaway machine. “New hardware, software, and applications are being released into public use daily, and analysts must create new methods to deal with each of them.”.

1. Why should digital forensics information be shared among law enforcement communities?

Digital forensics data should be shared amid the law enforcement communities since it is applied to both cases of crimes committed as well as against the digital assets and utilized in several physical crimes to bring together the evidence and proof of previous connections. Majority of the law enforcement agencies have diverse capabilities to carry out forensics which are at times enlisting the help of other agencies consultants to carry out analyses.  They are shared so that the new techniques are generated, ultimately checked and internally tested by the legal system to prove and generate forensic hypothesis. They are shared since the same methods are applied for other cases, the present proceeding ids guarded by the precedent of the previous case (Holt et al., 2017).

2. What does egocentric theory suggest about knowledge sharing?

Egocentric theory say that the informality based on knowledge transfer is a context that can cause the local pockets of the specialists and the redundancy of the energy geared across the general community at large. For instance, the digital forensics investigator found in Washington DC may end up spending 6 hours to increase the process meant to extract data saved in the slack space inside a hard drive sector. According to this theory the procedure might be shared amid the local colleagues such that the other DF expertise in diverse cities and areas will need to develop their own processes.

3. What behavior did the developers of NRDFI observe in terms of use of the system?

The behavior that the creators of NRDFI observed were that they developed it as a hub geared for knowledge sharing amid the law enforcements bodies. However, they realized that the site was locked down such that only the members of these bodies were in a position to view the content and the ability to share knowledge through uploading tools and documents that might have grown locally inside these departments such that the broader law enforcement bodies of practice might use their own contributions and minimize the redundancy of energy used. They also observed that the “Defence Cyber Crime Center, a co-sponsor of the NRDFI initiative, provided a wealth of knowledge documents and tools in order to seed the system with content (Dang-Nguyen et al., 2015).”

4. What additional features might enhance the use and value of such a KMS?

The additional feature that might enhance the value and the use of KMS incorporate new applications like the “Hash Link,” that can offer the DFI link to associates having a repository hash values which they would maybe require to advance their personal and their directory o that they facilitate the contacting of colleagues in an easier way from other departments or jurisdictions. Another additional feature was the integration of the calendar of events and newsfeed page that were incorporated into the DFI links in the response to the requirements of the users. Another thing is that “Increasingly, commercial software is also being hosted. Some were licensed through grants and others were provided by vendors, but all are free to vetted users of the law enforcement community (Cameron, 2018).”.

 

Conclusion.

The digital forensics investigator found in Washington DC may end up spending 6hours to increase the process meant to extract data saved in the slack space inside a hard drive sector. Egocentric theory say that the informality based on knowledge transfer is a context that can cause the local pockets of the specialists and the redundancy of the energy geared across the general community at large. The behavior that the creators of NRDFI observed were that they developed it as a hub geared for knowledge sharing amid the law enforcements bodies.

Diagram2

 

 

 

 

References

Cameron, L. (2018). Future of digital forensics faces six security challenges in fighting borderless cybercrime and dark web tools. Retrieved from https://www.computer.org/publications/tech-news/research/digital-forensics-security-challenges-cybercrime

Dang-Nguyen, D. T., Pasquini, C., Conotter, V., & Boato, G. (2015, March). Raise: A raw images dataset for digital image forensics. In Proceedings of the 6th ACM Multimedia Systems Conference (pp. 219-224). ACM. Retrieved from https://dl.acm.org/citation.cfm?id=2713194

Holt, T. J., Bossler, A. M., & Seigfried-Spellar, K. C. (2017). Cybercrime and digital forensics: An introduction. Routledge. Retrieved from https://www.taylorfrancis.com/books/9781315296975

Mahalakshmi, P., Puntambekar, V. P., Jain, A., & Singhania, R. (2019). Automatic Toll Tax Collection Using GSM. In Emerging Research in Computing, Information, Communication and Applications (pp. 635-644). Springer, Singapore. Retrieved from https://link.springer.com/chapter/10.1007/978-981-13-6001-5_54

She, Q. (2017). Institutional Innovation and Reforming Path of Tax Collection and Administration Concerning Natural Persons: Based on the new rules of the Revised Draft of the Law on Tax Collection and Administration (draft). International Taxation in China, (2), 3. Retrieved from http://en.cnki.com.cn/Article_en/CJFDTotal-SWSW201702003.htm

Sharda, R., Delen, D., & Turban, E. (2015) Business intelligence and analytics: Systems for decision support (10th ed.). Boston: Pearson.