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CIS 364 From Data Warehousing to Big Data

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Additional Content

Minimum Grade for Prerequisites

Unless otherwise indicated, a grade of C or higher is required for all prerequisite courses.

Course Description

Introduction to data warehousing architecture, data extraction, management, and load. Also covered are metadata management, dimensional modeling, data aggregation, data mining and Business Intelligence. Both SQL and NoSQL databases will be employed. Introduction to Big Data architecture, technologies and analytics. Selection of Big Data stores for disparate data sets, processing large data sets and querying them are also covered. Other topics such as Cloud computing, security management, machine learning, Agile methodology and Big Data tools will be introduced.

Units: 4
Degree Credit
Grade Option (Letter Grade or Pass/No Pass)
  • Lecture hours/semester: 48-54
  • Lab hours/semester: 48-54
  • Homework hours/semester: 96-108
Prerequisites: None
Corequisites: None
Transfer Credit: CSU , UC