Itc540 It Infrastructure Management Pg Assessment Answers

Question 1:

Define and explain the following terminologies:

Business intelligence (BI);

IT Agility;

SWOT analysis;

Strategic planning;

Enterprise architecture;

Management information systems;

MIS and DSS;

Cloud infrastructure;

Data and text mining;

DMS;

Big data.

Question 2:

Suggest a list of information technology (IT) Key Performance Indicators (KPIs) and outline the advantages and disadvantages associated with IT KPI.

Question 3:

What is SaaS and outline its benefit and disadvantages. Explain your answer.

Question 4:

Study "Business Continuity with Virtualization"  in your text book [Chapter 2, IT at Work 2.3] and answer the following questions:

What business risks had Liberty Wines faced?.

How does Liberty Wines’ IT infrastructure impact its competitive advantage?

How did server virtualisation benefit Liberty Wines and the environment?

Question 5:

Study "CASE 2 BUSINESS CASE: Financial Intelligence Fights Fraud" in your text book [Chapter 3] and answer the following questions:

What data and IT problems were limiting FinCEN’s ability to fight financial crime?

Describe the IT upgrades and capabilities needed by FinCEN in order to achieve its mission.

On what does financial intelligence depend?

Why is the ability to identify patterns and relationships critical to national security?

Research recent financial crimes that FinCEN has detected and disrupted. Explain the role of data analytics in crime detection.

Question 1:

Business intelligence: 

The “business intelligence” is a process which has been guided by technology. It is used for analyzing of information and displaying data that are actionable. It helps in making more enlightened business decisions for the end users, business managers and corporate executives (Richards, 2014).

I.T. Agility: 

The IT agility is referred to as an overall mind-set, viewpoint, process and culture together. It measures the pace in which any business reacts to the enterprise, threats and scopes having primary “agility indicators”.

SWOT analysis:

It is an effective and simple framework that helps to analyze the strength and weakness of an organization. It also considers the threats and scopes. It supports the concentration on the positive aspects, decrease the threats taking the best possible opportunities available.

Strategic Planning:

It is the process of the organizations that define the direction or strategy. It makes decisions to allocate the resources to undergo through the strategy. Moreover, it guides the imposition of the strategy.

Enterprise architecture:

It is a theoretical blueprint defining the operation and structure of a company. Its objective is to indicate the process in which the present and future aims could be successfully achieved.

Management information systems:

It is the computerized database, storing information regarding finance. It has been programmed to generate reports on the activities at regular basis. This is done at every platform of the management.

MIS and DSS:

The “Management Information System” or MIS and the “Decision support System” or DSS is used by various people at different contexts. The DSS is designed to deliver analysis that has relevance with the particular situations. The MIS on the other hand, has been implemented to processing of information efficiently (Aggarwal, 2016).

Cloud infrastructure:

It is a virtual infrastructure referring to the products or services that are demanded to get accessed or delivered.  This is done through internet or a network by the basic model of cloud computing, known as the IaaS or “Infrastructure as a Service”.

Data and text mining:

The high quality data are generally retrieved by the devising of trends and patterns via “statistical pattern learning”. The method to retrieve the data from text is known as the “Text data mining” (Pletscher-Frankild et al., 2015).

DMS:

The DMS or “Document Management System” helps in managing, tracking as storing documents and reducing papers. Most of them perform the task of “history tracking” or storing the records of different versions modified and developed by various users.

Big data:

It describes the huge quantity of information that could be either structured or unstructured. The primary aspect of big data concern with the task meant to be performed with the information. It can also be assesses for insights for better decisions. It also helps in improved strategic business approaches (Swan, 2013).

Question 2:

List of information technology (IT) Key Performance Indicators (KPIs):

The list goes like the following:

1. Process KPI
2. Input KPI
3. Output KPI
4. Leading KPI
5. Lagging KPI
6. Outcome KPI
7. Qualitative KPI
8. Quantitative KPI

Advantages associated with IT KPI:

The advantages are to identify the things easy to count and measure. Visibility on performance with strategic goal and agility in making decisions are done. There has been efficient management and increase in project flexibility. Lastly the focusing of employee’s attention on works is done (Parmenter, 2015). 

Disadvantages associated with IT KPI due to its features like:

There has been intention to improve future outcomes without any reference of external benchmarks and parties. No communication with external database is done. There has been overflowing of measurements and backward looking.

Question 3:

The SaaS or “Software as a Service” is the delivery and licensing model of a software. Here, the software has been licensed on the basis of subscription.

Benefits of SaaS:

It is due to the reason that the user has to pay according to the needs without buying hardware for hosting new applications leading to lower expense to access. Users get the application ready to utilize quickly, cutting down the time and allowing rapid prototyping. This reduces the time to benefit or rapid prototyping (Schaefer, 2014).

Disadvantages of SaaS:

Since the information has been kept in cloud, the safety is a major issue. SaaS model has been unsuitable for the applications demanding reply times within milliseconds. This lead to the latency issue (Ojala, 2013).

Question 4: 

1. Business risks faced by Liberty Wines:

As the business of Liberty Wines has been developing, the It facility became unable to control the growing volume of information. The systems became slow. They needed higher efforts for maintenance. This has indicated the decrease of productivity of the employees. Thus the central process of business has got affected. The affected areas include the inventory management and order processing. Liberty Wines was unable to deliver service the up to the mark of customer expectation. Thus they risked loss in upcoming business along with the present customers (Wright, 2014).

2. The impacts of IT infrastructure of Liberty Wines on the competitive advantage:

The impacts are reducing expenses on air conditioning, hardware replacement and power. It helps in developing stability and resilience by a “backup system”. It quickens the process of business by enabling the applications to run fast. Improvement of the bottom line is done. This is performed by providing the employees with better “customer service” with increase in productivity. Accommodation of future growth in business is also done quickly and easily (Wright, 2014).

All of the above aspects have been contributing to the benefits over the competitors by improving service, providing future growth and reducing costs.

3. Benefit of server virtualization to “Liberty Wines” and the environment:

The liberty Wines has decreased their amount of servers from ten to four. One of the servers was a portion of a “backup system”. This declined the costs of air conditioning and power consumption by sixty percent. This improved the bottom line. This reduced the “carbon foot-print”. The applications have been running quickly by better usage. In Turn, it culminated in better inventory management and customer service. The costs of hardware replacements, on the other hand were reduced about $70,000. Thus the servers were connected quickly and easily when required.

Question 5: 

1. Data and IT problems limiting FinCEN’s ability to fight financial crime:

The first problem is the data analytics issue. It states the information received by FinCEN has been invalid. It was also inconsistent and lacking validation before its submission. No rule of standard was followed for the reporting of information. Simple routines and small datasets are present for the data analysis.

Secondly there has been reporting deficiencies. It includes the offline reporting of system to different dependent agencies. Delaying of transforming and data cleaning are also considered. There has been slow detection of latest trends in the data analytics to disrupt the financial crimes (Sandoval, Horn & Hall, 2016).

2. IT upgrades and capabilities needed by FinCEN in order to achieve their mission:

A change in system has been undertaken by FinCEN, where huge amount of information from various sources has been analyzed and collected. The provide state, local and federal “law enforcement” to limited authorized customers (Network, 2014). They should be directly able to access the BSA data. They should also have huge number of queries into the database.

3. Factors on which the financial intelligence depend:

Some of the important considerations that shape the development of financial intelligence are financing laws of counter terrorism. It also includes need for authority to assess, share and receive the information. The existing law enforcement and anti-money laundering is also considered.

4. Ability in identifying the relationships and patterns critical to the national security:

The landscape of international strategy has been shaped by contradictory and complex forces. The drug cartels, vulnerabilities and international terrorism have added the information technology to turmoil (Network, 2014). The national security policies have been ambiguous, inconsistent and complicated. This has been due to the unpredictable characteristics of this international arena.

5.1. Recent financial crimes detected by FinCEN:

A terror hotline has been established by the FinCEN after the 9/11 occurred. It consisted of 853 tips that were intruded to the law enforcement by April 2004. On the other hand the financial institutions have filed 4294 SRS that involved possible financing of terrorists.

5.2. Role of data analytics in crime detection:

The “big data analytics” has been enabling the bank and other financial institutions to fight the risk of the financial crimes (Network, 2014). The organizations implement the “financial crime risk management strategy” which is a multi-faceted approach of analytics. This mitigates and detects the crimes built around the behavioral profiling.  

References:

Aggarwal, P. (2016). The Importance of Management Information System (MIS) and Decision Support System (DSS) in Decision-Making Process. Imperial Journal of Interdisciplinary Research, 2(12).

Network, F. C. E. (2014). Customer Due Diligence Requirements for Financial Institutions, RIN 1506-AB25 Dear Sir or Madam: The American Bankers Association (ABA) and BAFT 2 (the Associations) appreciate the opportunity to comment on the proposal by the Financial Crimes Enforcement Network (FinCEN) to clarify and strengthen customer due diligence (CDD) requirements. 3. Policy.

Ojala, A. (2013). Software-as-a-Service Revenue models. IT Professional, 15(3), 54-59.

Parmenter, D. (2015). Key performance indicators: developing, implementing, and using winning KPIs. John Wiley & Sons.

Pletscher-Frankild, S., Pallejà, A., Tsafou, K., Binder, J. X., & Jensen, L. J. (2015). DISEASES: Text mining and data integration of disease–gene associations. Methods, 74, 83-89.

Richards, G., Yeoh, W., Chong, A. Y. L., & Popovic, A. (2014, January). An empirical study of business intelligence impact on corporate performance management. In PACIS 2014: Proceedings of the Pacific Asia Conference on Information Systems 2014 (pp. 1-16). AIS eLiberary.

Sandoval, I., Horn, C., & Hall, M. (2016). Fincen requires financial institutions to obtain beneficial ownership information for legal entity customers. Journal of Investment Compliance, 17(4).

Schaefer, G. (2014). Evaluation of Business Benefits of SaaS-based Integrated Enterprise Systems for SMEs (Doctoral dissertation, University of Central Lancashire).

Swan, M. (2013). The quantified self: Fundamental disruption in big data science and biological discovery. Big Data, 1(2), 85-99.

Wright, A. (2014). ICT540: Enterprise Architect Blog. Management.