Project Plan Inception

Topics: Data analysis, Operating system, Chief executive officer Pages: 5 (1688 words) Published: February 1, 2013
Project Plan Inception
Tony Howell Jr.
January 14, 2012
Dr. Richard Burroughs

Project Plan Inception
As the newly Chief Information Officer (CIO) for our company I highly understand the drive to become a leading provider and advisor for data collection and analysis field. With the leading edge equipment Web analytics and operating systems data the future of the company looks promising. Becoming a foremost consultant of Web analytics in this market will be fortuitist to the company. The vision of the Chief Executive Officer (CEO) will be foreseen in the near future with the proper planning and execution of the plan.

To rehash the accomplishments and aspirations on the future of the company. The company is currently a $25 million dollar data collection and analysis company that has been operating less than two (2) years. There are twenty employees on one floor to comprise the company faculty. The vision of the CEO is to grow by 60% over the next eighteen (18) months. Expand to three (3) floors within six (6) months that would consist of the new leverage department into cloud computing technologies and Software-as-a-Service (SaaS). These are the vision that the CEO has to improving the abilities of this company and as the CIO, I conquer with him. So this is beginning of the planning process to accomplish our task. With this enhancement of our technology our goal is to be able to support Corporations and Banking industries.

The company is into data collection and analysis in which certain utilities are used to perform these duties. The data that is collected is Attribute data which is presence or absence of a characteristic and Variables data that can be specific measurement. The descriptions of the two types are as followed: * Attribute data give you counts representing the presence or absence of a characteristic or defect. These counts are based on the occurrence of discrete events. * Variables data are based on measurement of a key quality characteristic produced by the process. Such measurements might include length, width, time, weight, or temperature, to name a few. This data may be SP-base data that can be collected over system traffic that we are analyzing. Panel data (also known as longitudinal or cross sectional time-series data) is a dataset in which the behavior of entities is observed across time. Monitoring network upload and download data of computers or network devices (DVR, Internet radio, wireless connections, etc.). Online Monitoring Data is gathering information on the internet that the customers are producing and analyzing the essential output that can contribute to the customer. When we conduct analysis of a customer network we have two kinds of data; Quantitative data refer to the information that is collected as, or can be translated into, numbers, which can then be displayed and analyzed mathematically. Qualitative data are collected as descriptions, anecdotes, opinions, quotes, interpretations, etc., and are generally either not able to be reduced to numbers, or are considered more valuable or informative if left as narratives. The following describes both: * Quantitative data - typically collected directly as numbers, the frequency (rate, duration) of specific behaviors or conditions, test scores (e.g., scores/levels of knowledge, skill, etc.), survey results (e.g., reported behavior, or outcomes to environmental conditions; ratings of satisfaction, stress, etc.), numbers or percentages of people with certain characteristics in a population (diagnosed with diabetes, unemployed, Spanish-speaking, under age 14, grade of school completed, etc.) * Qualitative data - qualitative information tends to be “soft,” meaning it can’t always be reduced to something definite. Qualitative data can sometimes be changed into numbers, usually by counting the number of times specific things occur in the course of observations or interviews, or by assigning numbers...
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