DATA 215 - Data Engineering

Credits: 5
Variable Credit Course: No

Lecture Hours: 55
Lab Hours: 0
Worksite/Clinical Hours: 0
Other Hours (LIA/Internships): 0

Course Description: Explore foundational concepts and technologies in big data engineering. Learn about big data pipelines, storage, and processing, as well as the architecture of big data systems. Topics include cloud infrastructure, APIs for data access and integration, and ETL/ELT processes for data ingestion, extraction, and transformation. The automation and maintenance of data pipelines for reporting purposes is emphasized.

Prerequisite: DATA 115 and DATA 210 with a C or higher; or Dept. Chair permission.
Meets FQE Requirement: No
Integrative Experience Requirement: No

Student Learning Outcomes

Define data extraction methods and tools including APIs and data scraping.
Describe the process to build and manage data pipelines including data ingestion.
Design and deploy a basic ETL/ELT process.
Describe the process to automate and maintain data pipelines for reporting purposes.
PROGRAM OUTCOME: Prepare quality datasets through data extraction, data ingestion, data cleaning, and data transformation.

Course Contents

Data pipelines, storage, and processing.
Cloud infrastructure.
APIs.
ETL/ELT processes.
Automation and maintenance of data pipelines.

Instructional Units: 5