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Detailed Course Information


Fall 2020
Jul 18, 2024
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CS 50024 - Data Engineering II
Credit Hours: 1.00. This course introduces students to the fundamentals of database management systems (DBMS) from a user's perspective. The principles of modeling an enterprise using Entity-Relationship diagrams and transforming the model into a relational or NoSQL database are illustrated through a range of examples. The SQL language is used to create, query, aggregate, and update a relational database. NOSQL databases and the related data models (column, graph, and document-based) are introduced. Experience in Python Programming is required. Typically offered Fall Spring Summer.
1.000 Credit hours

Syllabus Available
Levels: Undergraduate, Graduate, Professional
Schedule Types: Distance Learning

Offered By: College of Science
Department: Computer Science

Course Attributes:
Upper Division

May be offered at any of the following campuses:     
      West Lafayette

Learning Outcomes: 1. Carry out database design steps from conceptual to logical to physical design. 2. Use SQL commands to define the structure of a relational database, populate, update and delete data in the database, retrieve data having specified characteristics, and specify access control. 3. Explain the differences, advantages, and disadvantages of relational and NOSQL databases. 4. Describe features of relational databases not needed in big data applications. 5. Create a document-based, NOSQL database like mongoDB and movie data from an SQL to a NOSQL database. 6. Understand the benefits and downsides of creating index structures on query performance for relational, and NOSQL databases. 7. Explain the difference between hash indices and B-tree indices. 8. Analyze large data sets created from piecing together multiple data files through the application of SQL queries.

Must be enrolled in one of the following Levels:     

Short Title: Data Engineering II

Course Configurations:

Configuration 1: 1.0 Credit
Schedule Type Weekly Contact Hours Instructional Credit Distribution
Distance Learning 0 1.0

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