Data Analytics is a technically-oriented program that 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.
Declaring Minors
To be eligible to declare minors, students must have already completed the required
coursework, or be able to complete it intheir final terms without requiring waivers,
substitutions, or directed study courses, unless they are approved in advance by thedepartment
chair, program director, or dean.
Students may declare minors when they have completed the required coursework, or after
the “Last Day to Drop Course with-out Tuition Charge” (per the Academic Calendar)
for their final terms.
Students may not declare the same minor as their major (i.e., students majoring in
accounting may not also declare minors inaccounting.) Students may declare up to two
minors in a given degree program. Students seeking to declare more than twominors
will be required to appeal to the dean for approval. Students’ diplomas will list
the minors that they had successfully completed at the time their degrees were conferred.
Students may not declare additional minors after their degrees have beenconferred.
Students may select from the following minors:
- Accounting Minor
- Business Minor
- Data Analytics Minor
- Finance Minor
- Human Resource Management Minor
- Information Technology Minor
- International Business Minor
- Law Minor
- Literature Minor
- Management Minor
- Marketing Minor
- Operations and Supply Chain Management Minor
- Organizational Leadership and Human Skills Development Minor
- Psychology Minor
- Public Administration Minor
Data Analytics Minor
This minor teaches students how to use tools to extract, categorize, and examine large
amounts of information in order to draw insights that can help organizations make
betterinformed business decisions. Instruction is relevant and applicable to a broad
range of industries and disciplines, including marketing, management, finance, financial
planning, project management, human resources, information technology, operations,
supply chain management, and others. The curriculum covers a breadth of data analytics
tools and concepts, including dashboards, R Language, SAS, Data Mining, and SQL, among
others.
Required Courses - 15 units
Select five of the following:
- DATA 50
- Introduction to Business & Data Analytics
- DATA 101
- Data Visualization for Business
- DATA 102
- Business Intelligence & Data Mining
- DATA 103
- Data Analytics Using SAS
- DATA 104
- Introduction to R Programming for Data Analysis
- DATA 110
- Introduction to Python Programming for Machine Learning
- DATA 115
- Introduction to Relational Databases & SQL
- DATA 120
- Introduction to Big Data
- ITM 108
- Introduction to Relational Databases
- MATH 104
- Quantitative Fluency for Business Managers and Leaders
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
- Tina Jackson, Senior Adjunct Professor
- Patricia Knight, Adjunct Professor
- Steven Lee, Adjunct Professor
- Christopher Lynch, Adjunct Professor
- Roldan Mallorca, Adjunct Professor
- Alan R. Roper, Senior Adjunct Professor
- Walter Stevenson, Professor
- Jan Wilson, Senior Adjunct Professor
- Jeffrey D. Yergler, Associate Professor, Management & Department Chair, Management
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