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Data Analytics is a technically-oriented program which will help students build a tool-set of data analytics skills. Students will gain real-world, practical training from leading-edge industry professionals who place data analytics within a business and enterprise context, ensuring that students become well-rounded professionals themselves.

This program will help the adult undergraduate student acquire an understanding of, and competency in, current trends in data analytics, applying them to generate insights from data in a variety of business and organizational contexts. Students will learn about Big Data, master the technical aspects of data analytics, and understand the relevance of this type of analysis to business and organizations. Students will benefit from a curriculum that leverages critical thinking, information literacy, and effective communication skills to help students increase their professional marketability. These skills will advance students' ability to analyze business problems, put those problems in perspective, and clearly communicate insights gained from data analyses.

GGU is excited to offer six new nine-unit data analytics certificates that can be completed in as little as one semester. Learn in-demand skills in with some of the most-used tools: Tableau, HQL, Python, R, SAS, and SQL.

TOTAL UNITS — 123

39 GENERAL EDUCATION UNITS

REQUIRED - 18 UNITS

UGP 10
Gateway to Success (to be taken in the first term of the program)
CRTH 10
Critical Thinking
ENGL 1A
Expository Writing
ENGL 1B
Research Writing
ENGL 120
Business Writing
AND
one of the following:
COMM 35
Speech Communication
COMM 40
Understanding Communication

LIBERAL STUDIES CORE - 21 UNITS

ARTS 50
Contemporary Arts & Culture (or any other SOSC course)
HIST 50
Contemporary American Economic History (or any other HIST course)
HUM 50
Examining the Humanities (or any other HUM course)
LIT 50
Principles of Storytelling (or any other LIT course)
PHIL 50
Professional & Personal Ethics (or any other PHIL course)
SCI 50
Science, Technology & Social Change (or any other SCI course)
SOSC 50
American Government in the 21st Century (or any other SOSC course)
OR
 
PSYCH 10
Psychology for Personal & Professional Success (or any other PSYCH course)

MAJORREQUIREMENTS — 54 UNITS

FOUNDATION - 9 UNITS

MATH 30
College Algebra
MATH 40
Statistics
MATH 104
Applied Regression Analysis

BUSINESS - 15 UNITS

Any five of the following:
FI 100
Financial Management
MGT 100
The Manager as Communicator
MGT 140
Management Principles
MGT 145
Law of Contracts, Sales, & Commercial Transactions
MGT 179
Introduction to International Business
MKT 100
Principles of Marketing
OP 100
Principles of Operations Management

DATA ANALYTICS - 30 UNITS

DATA 50
Introduction to Business & Data Analytics
DATA 101
Creating Dashboards & Scorecards
DATA 102
Business Intelligence & Data Mining
DATA 103
Data Analytics Using SAS
DATA 104
Introduction to Social Media Data Analytics
DATA 110
Introduction to Machine Learning & Natural Language Processing
DATA 115
Introduction to Relational Databases & SQL
DATA 120
Introduction to Big Data
DATA 125
Artificial Intelligence in Business
DATA 190
Capstone

ELECTIVE COURSES - 30 UNITS

Ten 3-unit upper or lower-division courses from any subject.


Each course listed carries three semester units of credit, unless otherwise noted.

ADMISSION REQUIREMENTS

LEARNING OUTCOMES

Students who complete the Bachelor of Science in Data Analytics, including the general education program, will be able to:
  • Understand and apply the fundamentals of data analytics to real-world business problems.
  • Leverage familiarity with the appropriate use of key analytic languages/methods/tools, including R, Python, SQL, NOSQL, SAS, and Tableau, to address business problems, and be able to articulate the advantages and limitations of each one in a variety of business and organizational contexts.
  • Demonstrate ability to identify, acquire, cleanse and effectively organize data for analysis.
  • Demonstrate a critical understanding of the utility of data analytics tools using data visualization methods in extracting value from data sets.
  • Recognize the various challenges (social, economic, and political) represented by the Big Data ecosystem and describe the use of supporting technologies to address these challenges.
  • Explain the differences between structured and unstructured data and be able to deploy them appropriately, aligning the use of each with relevant business applications.
  • Describe the different approaches to machine learning and the implications of each one, demonstrating the application of the most common algorithms.
  • Explain the use of Natural Language Processing, identifying and implementing potential applications and appropriate supporting tools.
  • Use storytelling with visual outcomes from analytics to communicate effectively to members of the business community and others, both expert and non-expert, in a variety of settings and formats.
  • Demonstrate an understanding of the business implications, relevance and applicability of data analytics and statistical inferences.
  • Identify opportunities, needs and constraints for data analytics within organizational contexts.

MANAGEMENT, HUMAN RESOURCES AND INTERNATIONAL BUSINESS DEPARTMENT

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