Data Warehouse Pros and Cons Analysis

IT 675 Milestone One Rubric: Data Warehouse Pros and Cons Analysis Rubric The final project for this course is a two-part project: an executive presentation and a technical proposal. The final project presents a detailed scenario regarding the merger of two insurance companies. For the project, the student is positioned as the chief information officer (CIO) and is asked to lead an initiative to merge the data infrastructures of both insurance companies into a single consolidated data warehouse. For this milestone (due in Module Two), you will submit your data warehouse pros and cons analysis. Review the scenario for the final assessment. Using the scenario, develop a pros and cons analysis of implementing a data warehouse. Include the following elements: 1) cost and return on investment (ROI), 2) required resources, 3) informational value, and 4) limitations. The following critical elements will be addressed in this submission: Pros and Cons:

a) Cost and Return on Investment: How is the cost of a data warehouse worth the investment? What type of information can a data warehouse provide that would make the cost more acceptable? How will the organization benefit from a data warehouse? Are there any negative consequences of having a data warehouse? Which specific operational areas will feel the benefits?

b) Required Resources: What are the costs associated with a data warehouse? Will any additional staff be required to maintain and support the data warehouse? Be sure to explain the importance of each resource you identify.

c) Informational Value: How can the information in a data warehouse add value to the organization? What specific business opportunities could be illuminated and how would the use of a DBMS help solve business problems?

d) Limitations: What are some functions that a data warehouse cannot perform? How scalable is a data warehouse? How can the organization overcome these obstacles to ensure data quality? Support your conclusions.

Requirements of Submission: Written components of projects must follow these formatting guidelines when applicable: double spacing, 12-point Times New Roman font, one-inch margins, and discipline-appropriate citations.

Critical Elements Exemplary (100%) Proficient (90%) Needs Improvement (75%) Not Evident (0%) Value

Cost and Return on Investment

Meets “Proficient” criteria and analysis of cost versus value is centered on the particular business environment of the scenario

Provides a detailed and logical analysis of the cost of integrating systems versus the value of a data warehouse

Discusses the cost of integrating systems versus value of a data warehouse, but lacks necessary detail for a comprehensive analysis

Does not discuss the cost of integrating systems versus the value of a data warehouse

20

Required Resources Meets “Proficient” criteria and takes the analysis a step further by expounding on the opportunities that may be presented by attaining such resources

Accurately analyzes the particular costs, labor, equipment, and other resources that may be required and explains the importance of each

Analyzes the particular costs, labor, equipment, and other resources that may be required, but not accurately, or the importance of each is not explained accurately

Does not analyze the particular costs, labor, equipment, and other resources that may be required

20

Informational Value Meets “Proficient” criteria and provides specific details and examples that highlight the value of data warehouses for business contexts

Accurately analyzes the business opportunities and problem-solving capabilities of the information that can be housed in a data warehouse specific to the scenario

Analyzes the business opportunities and problem- solving capabilities of the information that can be housed in a data warehouse, but not accurately or specifically to the scenario

Does not analyze the business opportunities and problem- solving capabilities of the information that can be housed in a data warehouse

20

Data Limitations Meets “Proficient” criteria and support includes relevant examples and quality sources

Describes common methods for overcoming possible limitations of integrating, scaling, and ensuring data quality with support

Describes methods for overcoming possible limitations of integrating, scaling, and ensuring data quality, but is not comprehensive or lacks relevant examples

Does not describe methods for overcoming possible limitations of integrating, scaling, and ensuring data quality

20

Articulation of Response

Submission is free of errors related to citations, grammar, spelling, syntax, and organization, and is presented in a professional and easy-to- read format

Submission has no major errors related to citations, grammar, spelling, syntax, or organization

Submission has major errors related to citations, grammar, spelling, syntax, or organization that negatively impact readability and articulation of main ideas

Submission has critical errors related to citations, grammar, spelling, syntax, or organization that prevent understanding of ideas

20

Earned Total 100%