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Week 5 Data Management Research Paper

Week 5 Data Management Research Paper

Q Your research paper, based on the topic you selected in week 3, is due this week. Submit a research paper regarding an aspect of data management. Use this website Links to an external site.to help with APA formatting. Here is a sample paper in APA format Links to an external site.. Requirements: The paper must concentrate on a topic chosen in week 3. The textbook must be used as one of the minimum three references for the paper. APA 7th edition format should be followed in regard to the completion of this paper. That means there must be a title page and a separate reference page. The paper must be double spaced using Times New Roman 12 pt. font. Not counting the title and reference pages, the body of the research paper should be 5 - 7 pages. A minimum of three references should be cited in the body of the paper and shown on the reference page. Submit your paper in MS Word format via the assignment link. Resources: • Database Systems, 13e Textbook in MindTap • Wilmington University LibraryLinks to an external site. • Google ScholarLinks to an external site. Rubric Data Management Research Paper Rubric (1) Data Management Research Paper Rubric (1) Criteria Ratings Pts This criterion is linked to a Learning OutcomeCritical Thinking 20 pts Excellent Main points are clear and well developed. Logical development is easy to follow. 18 pts Good Main points are clear and well developed. Evidence and detail provide strong support for the data management project 16 pts Satisfactory Main points are clear and developed. Evidence and detail adequately support the data management project. 14 pts Unsatisfactory Main points are clear but not developed. More supporting evidence and detail are needed. 20 pts This criterion is linked to a Learning OutcomeAnalysis and Interpretation 20 pts Excellent Ability to analyze & interpret data is superior. 18 pts Good Ability to analyze & interpret data is proficient. 16 pts Satisfactory Ability to analyze & interpret data is basic. 14 pts Unsatisfactory Ability to analyze & interpret data is emerging. 20 pts This criterion is linked to a Learning OutcomeKnowledge of Content 20 pts Excellent Exceeds requirements in demonstrating strong knowledge of content and depth. 18 pts Good Knowledge of content and depth are appropriately reflected in document. 16 pts Satisfactory Knowledge of content and depth are satisfactory. 14 pts Unsatisfactory Some knowledge of content and depth are evident. 20 pts This criterion is linked to a Learning OutcomeAssignment Purpose 20 pts Excellent Work stands out as exemplary, is accurately detailed. The data management project is appropriately addressed. 18 pts Good Work is accurately detailed. The data management project is adequately addressed. 16 pts Satisfactory Work reflects the assignment purpose. The data management project has most if not all of the components addressed. 14 pts Unsatisfactory Work rarely reflects the assignment purpose. The data management project is only half completed. 20 pts This criterion is linked to a Learning OutcomeWriting Mechanics/Submission 20 pts Excellent Writing demonstrates a sophisticated clarity, conciseness, and correctness; includes thorough details and relevant data and information; extremely well-organized. Uses APA guidelines accurately and consistently to cite sources. 18 pts Good Writing is accomplished in terms of clarity and conciseness, and contains only a few errors; includes sufficient details and relevant data and information; well-organized. Uses APA guidelines with minor violations to cite sources. 16 pts Satisfactory Knowledge of content and depth are satisfactory. 14 pts Unsatisfactory Writing is unfocused, rambling, or contains serious errors; lacks detail and relevant data and information; poorly organized. Uses APA guidelines with major violations to cite sources. 20 pts Total Points: 100

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In a company with enormous data and big analytics, their dealing becomes very difficult. That is why data marts are used so that the data can be carefully converted into insights of the data. Data warehouses are dealing massive amounts of data, whereas data analytics use data that is easy to find and readily available. It is not worth it that a businessman spends his precious time finding the data. This is not practical, and that is why efficient companies use data marts. A data mart is a database oriented around a single subject and usually a partition of the greater data warehouse (Sharma, 2021).