Milestone Three: Data Integrity and Scrubbing Portion

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Computer Science

Description

Submit the data integrity and scrubbing portion of your plan. Review the scenario for the final assessment. Using the scenario, develop this portion of the project plan. To meet requirements, you will need to address the four aspects of this subsection of the proposal, which are as follows: 1) data integrity, 2) primary key(s), 3) customer data, and 4) duplicate data.

For additional details, please refer to the Final Project Guidelines and Rubric document and the Milestone Three Rubric document.

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Milestone Three Rubric: Data Integrity and Scrubbing Portion 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 Six), you will submit your data integrity and scrubbing portion of the plan. Review the scenario for the final assessment. Using the scenario, develop this portion of the project plan. To meet requirements you will need to address the four aspects of this subsection of the proposal, which are as follows: 1) data integrity, 2) primary key(s), 3) customer data, and 4) duplicate data. The following critical elements will be addressed in this submission: Data Integration and Scrubbing: a) Data Integrity: How will you combine date fields with various formats (i.e., MMDDYYYY vs. DDMMYYYY)? What other data issues will need to be addressed? b) Primary Key(s): What will you use as a unique identifier to combine the records? What primary keys, foreign keys, and indexes will you need to create? c) Customer Data: Once the data is merged into the data warehouse, how will you be able to differentiate customers from Virtual World Insurance Company and customers from Maxon Insurance Company? d) Duplicate Data: How will you eliminate duplicate records in the database to ensure data quality? 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 Data Integration and Scrubbing: Data Integrity Meets “Proficient” criteria and methods described are the best methods for ensuring data integrity for the given scenario and specific issue Articulates the correct methods for combining data fields with various formats to ensure data is not lost or compromised Articulates methods for combining data fields with various formats, but methods are not correct for ensuring data is not lost or compromised Does not articulate methods for combining data fields with various formats 20 Data Integration and Scrubbing: Primary Keys Meets “Proficient” criteria and identified keys and indexes are the most appropriate for each of their designated purposes within the data warehouse Articulates appropriate primary keys, foreign keys, and indexes for creation that will ensure a clear and accurate warehouse Articulates primary keys, foreign Does not articulate primary keys, and indexes necessary, but keys, foreign keys, and indexes not all will ensure a clear and necessary accurate warehouse 20 Data Integration and Scrubbing: Customer Data Meets “Proficient” criteria and articulated methods are the most appropriate given the accompanying explanation, accompanying scenario, and integration issues that have been identified in the proposal Articulates plausible methods for differentiating customer data from each company after data is merged Articulates methods for differentiating customer data from each company after data is merged, but not all methods are plausible, or necessary detail is left out of explanation Does not articulate methods for differentiating between customer data from each company after data is merged 20 Data Integration and Scrubbing: Duplicate Data Meets “Proficient” criteria and identified strategies are the most appropriate given the accompanying explanation, accompanying scenario, and integration issues that have been identified in the proposal Articulates valid, plausible strategies for eliminating duplicate records and ensuring data quality and accuracy Articulates strategies for eliminating duplicate records and ensuring data quality and accuracy, but not all strategies are valid or plausible Does not articulate strategies for eliminating duplicate records to ensure data quality and accuracy 20 Articulation of Response Submission is free of errors related to citations, grammar, spelling, syntax, and organization, and is presented in a professional and easytoread 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%
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Explanation & Answer

Attached.

DATA INTEGRITY AND
SCRUBBING PORTION
NAME:
COURSE:

PROFESSOR:
DATE:

Data integrity : methods of combining data fields
❖Joining method
❖Relating method

❖Join table...


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