2021-2022 Catalog [ARCHIVED CATALOG]
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DBMS 130 - Data Management using Structured Query Language
PREREQUISITES: DBMS 110 - Introduction to Data Analytics .
PROGRAM: Data Analytics
CREDIT HOURS: 3
LECTURE HOURS: 2
LAB HOURS: 2
DATE OF LAST REVISION: Fall, 2020
Students are introduced to Structured Query Language (SQL) which is a database computer language used to manage, query, retrieve and manipulate data. Students are introduced to SQL as a high level tool in the management of data in client and server database environments. Students will use relational database management systems to develop SQL skills in a lab environment.
MAJOR COURSE LEARNING OBJECTIVES: Upon successful completion of this course the student will be able to:
- Discuss procedural versus declarative languages.
- Utilize SQL to identify and describe the structure and contents of a database.
- Design DDL Statements to Create and Manage Tables.
- Implement keys and constraints to ensure data and referential integrity.
- Utilize SQL DML commands to insert, update, and delete data.
- Utilize SQL commands to retrieve data from single and multiple tables.
- Employ Set Operators to combine the results of multiple queries.
- Design and execute table joins and aggregate functions.
- Modify SQL commands to restrict and sort data.
- Use single-row and multiple-row subqueries to improve query performance.
- Differentiate between Single-Row and Multi-Row functions.
- Develop and alter stored procedures and user-defined functions (UDFs).
- Demonstrate how to extract, transform, and load data into various data systems.
- Compare performance and usage of relational vs. big data and NoSQL systems.
- Implement and utilize scripts in order to declare and enumerate schema objects.
COURSE CONTENT: Topical areas of study include - Define a database using SQL
Data Types
DDL - Database Design Language
Conditional Expressions
DML - Database Manipulation Language
Common Table Expressions (CTS’s)
Data and Referential Integrity
DCL - Database Control Language
Database Manipulation
SQL SELECT statements
Single and multiple-table queries
Aggregate Functions
Joins - Unions, Left, Right, Inner, Outer
Indexes
Views
Synonyms
Transactions
Nested Queries
Normalization
Big Data
Course Addendum - Syllabus (Click to expand)
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