Information Systems Strategic Planning

Information Systems Strategic Planning

Part 1: Data Section

The data section provides information to the companys revenues levels from 2012 to 2014. The data are presented by classifying different periods in quarters and the amount of revenues in billions of US dollars. The data are a good measure of the companys performance over the last two years. Most importantly, the percentage change of revenues in each quarter illustrates how external factors would influence the companys revenues in different quarters of the year (Clarke, 2012).

Table 1.

Trend of Revenues from 2012 to 2014.

Period (Quarters)	Amount of Revenues (in $ billions)	Percentage Change (% Increase/Decrease)
Q2-12	110	-
Q3-12	115	4.5
Q4-12	112	(2.6)
Q1-13	125	11.6
Q2-13	115	(8.0)
Q3-13	118	2.6
Q4-13	116	(1.7)
Q1-14	135	16.4
Q2-14	113	(22)
Q2-14	124	11

The data warehouse involves uploading of the revenues data to the companys operational systems. The percentage in the revenue level would help in the data warehouse. For instance, in the fourth quarter the company records a reduction in the company revenues. This can be observed from the reduction of revenues in the fourth quarters of years 2012, 2013, and 2014. However, the first quarter records a substantial increase in the companys revenues. Such analysis can be stored into the companys data warehouse for future use in the company. In order to make informed decisions, the company requires appropriate data mining mechanisms to interpret the revenue data of the company. Some of the ways of data mining include calculation of the mean and variances, understanding the trend of the data or even observing the distribution of the revenues over the year.

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The data mining approach helps to tackle difficult business challenges in organizations. In the given case, the data mining practice seeks to understand sales levels of the company in different periods of the year within two years. Understanding of the revenues levels within two years helps the company to make proper adjustments aimed at stabilizing the revenues levels over different years. Availability of the revenues data is also significant in ensuring that an effective data mining process is conducted. Managers should ensure that required information is available for making appropriate analysis.

Another key data mining issue is the need to understand the costs incurred in the organization. The level of costs affects performance of the business in many ways. The model is required to reflect differences between customer units in order to predict appropriate offsetting methods and reduction of losses (Chen, Mocker, Preston, & Teubner, 2010). This forms a part of the overall strategic planning of the organization. Even though managers might be required to carry out a prototype of the data section, the data mining approach helps to save time thanks to its accurate analytic concepts (Baltzan, 2014). Data mining should be specific in its analysis. In the given case, the data mining will try to explain differences between revenues within different quarters of the trading years-management analysis. The company relies on results of the data mining mechanisms that provide relevant revenue patterns. The efforts are aimed at ensuring that operational costs are kept low. Such practices improve recording of the revenues patterns and the internal operations information. Therefore, the data mining concepts of understanding revenue trends provide quality business intelligence (BI) for future decision-making.

Part 2

The concept of data security explains the need to keep data from authorized access. It allows for confidentiality in order to protect integrity and corporate data. Organizations require appropriate tools to make the data of the company secure. An example of data security tool is the use of authentication in terms of passwords and different levels of clearance. An accounting clerk would require permission from the superiors in order to access information above his/her clearance level. The permission includes access to passwords and data above the clearance level. The use of authentication helps to ensure confidential information is allowed to be accessed by certain persons within the organization. Password authentication would involve an ability to log into various applications within organizations computer systems (Baltzan, 2014). The authentication is awarded openly to promote transparency and accountability to all personnel in terms of data security. Every employee is required to ensure data security and confidentiality by using authentication within their data access levels. Any breach of data security may result in a severe punishment as well as the loss of a job.

Data security is a significant aspect of every organization as it protects trade secrets and value of the organization. Other examples of user authentication include the use of a smart card and finger print verification. Data security tools ensure that only limited personnel can access all organizations files and records. Some data could only be accessed by senior managers while accounting clerks have certain authentication powers relating to accounting information. Accounting clerks should ensure that finances of the company are used properly. Thus, accounting clerks have passwords to accounting and financial information of the company.

Data security helps to prevent hacking and alteration of the companys information and data. For example, accounting clerks have certain authentication powers to prevent senior managers from altering financial information of the company. Thus, the data security mechanism prevents different parties in the organization from manipulating the data and information for their personal gains. It should be noted that accounting clerks may be willing to alter some facts in systems to cover their mistakes. Authentication ensures that any access to the system is recorded for accountability purposes (Aleksic-Maric & Ilic, 2012).

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