Knowledge and Data Management - auce

Knowledge and Data Management

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Course Code:

BMIS380

Course Hours:

45

Contact Hours / Week:

3

Prerequisite:

BMIS310

Co-requisite:

None

Course Description:

This course focuses on the design and management of data in the organization. Data form the basis of modern business analytics and decision making in organizations. This course will explore all aspects of data, including strategic planning, modeling and representation, semantics, quality, and other related issues.

This course will provide a basis for data and database management in today’s enterprise. It will focus on the relational database model using MySQL. It will present the student with many key concepts relating to database technology, how database technology is being used, and the opportunity to put these concepts to practice. This course will cover database management system (DBMS) concepts, database architecture, data design using entity-relationship (ER) modeling, data storage, file organization, the SQL language, normalization, data integrity, database security, data warehousing, and related emerging technologies.

 

Course Learning Outcomes:

 

After taking this course, students will be able to:

  1. Understand the role of data in the competitiveness of organizations
  2. Elucidate on the various data management functions and strategies
  3. Describe and elucidate on the various types of database schemas
  4. Analyze functional dependencies and normalize data
  5. Design relational databases
  6. Build SQL queries
  7. Develop and critique entity-relationship (ER) data models
  8. Describe systems theory and layered models. Build information and object-oriented models
  9. Elucidate advanced data modeling issues- e.g., temporal data modeling, meta-data, etc.
  10. Identify and analyze data quality in a business context
  11. Develop and evaluate strategic data plans; e.g., Master data management plan and Enterprise data strategy & models
  12. Understand the growing importance and issues associated with data warehousing, business intelligence and analytics, and big data.

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