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CSI 111 Business Intelligence And Data Warehouses

  1. Assignment 3: Business Intelligence and Data Warehouses

    Due Week 9 

    Businesses today are extremely reliant on large amounts of data for making intelligent business decisions. Likewise, the data warehouses are often structured in a manner that optimizes processing large amounts of data.

    Write a two to three (2-3) page paper in which you:

    1. Outline the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.
    2. Outline the main differences between database requirements for operational data and for decision support data.
    3. Describe three (3) examples in which databases could be used to support decision making in a large organizational environment.
    4. Describe three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large

      organizational environment.
    5. Use at least three (3) quality resources in this assignment. Note: Wikipedia and similar Websites do not qualify as quality resources.

    Your assignment must follow these formatting requirements:

    • Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides; citations and references must follow APA or school-specific format. Check with your professor for any additional instructions.
    • Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date. The cover page and the reference page are not included in the required assignment page length. 

    The specific course learning outcomes associated with this assignment are:

    • Describe the role of databases and database management systems in managing organizational data and information.
    • Distinguish the role of databases and database

      management systems in the context of enterprise systems.
    • Use technology and information resources to research issues in database systems.
    • Write clearly and concisely about relational database management systems using proper writing mechanics and technical style conventions.

    Click here to view the grading rubric for this assignment.

     

 GRADING FOR

THIS ASSIGNMENT WILL BE BASED ON ANSWER QUALITY, LOGIC / ORGANIZATION OF THE PAPER, AND LANGUAGE AND WRITING SKILLS, USING THE FOLLOWING RUBRIC.


Points: 100

Assignment 3: Business Intelligence and Data Warehouses

Criteria

 

Unacceptable

Below 60% F

Meets Minimum Expectations

60-69% D

 

Fair

70-79% C

 

Proficient

80-89% B


width="97">

 

Exemplary

90-100% A

1. Outline the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Weight: 21%

Did not submit or incompletelyoutlined the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Insufficiently outlined the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Partially outlined the main differences between the structure of a



relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Satisfactorily outlined the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Thoroughly outlined the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

2. Outline the main differences between database requirements for operational data and for decision support data.
Weight: 21%

Did not submit or incompletelyoutlined the main differences between database requirements for operational data and for decision



support data.

Insufficiently outlined the main differences between database requirements for operational data and for decision support data.

Partially outlined the main differences between database requirements for operational data and for decision support data.

Satisfactorily outlined the main differences between database requirements for operational data and for decision support data.

Thoroughly outlined the main differences between database requirements for operational data and for decision support data.

3. Describe three (3) examples in which databases could be used to support decision making in a large organizational environment.

Weight: 21%

Did not submit or incompletelydescribed three (3) examples in which databases could be



used to support decision making in a large organizational environment.

Insufficiently described three (3) examples in which databases could be used to support decision making in a large organizational environment.

Partially described three (3) examples in which databases could be used to support decision making in a large organizational environment.

Satisfactorily described three (3) examples in which databases could be used to support decision making in a large organizational environment.

Thoroughly described three (3) examples in which databases could be used to support decision making in a large organizational environment.

4. Describe three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational



environment.

Weight: 21%

Did not submit or incompletelydescribed three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

Insufficiently described three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

Partially described three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

Satisfactorily described three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

Thoroughly described three (3)



examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

5. 3 references

Weight: 6%

No references provided

Does not meet the required number of references; all references poor quality choices.

Does not meet the required number of references; some references poor quality choices.

Meets number of required references; all references high quality choices.

Exceeds number of required references; all references high quality choices.

6. Clarity, writing mechanics, and formatting requirements

Weight: 10%

More than 8 errors present


width="97">

7-8 errors present

5-6 errors present

3-4 errors present

0-2 errors present


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