Skip to main content
  • Cybersecurity, Virtualization and Forensics

    Delivery: A mix of daytime, evening and online courses.
    Start: Fall, Spring, or Summer; Full- or Part-Time.

    Applied Big Data Analytics – Associate in Applied Science Degree (60 credits)

About the Program

The Applied Big Data Analytics AAS degree prepares students to enter into the rapidly growing industry of Big Data Analytics. While in the program, students will learn the process of examining large and varied data sets to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more-informed business decisions.  

The demand for employees in the big data analytics field is exploding! According to the International Data Corporation (IDC), the Big Data Analytics market will reach $125 billion worldwide in 2017—and is projected to grow to $203 billion by 2020.  

Organizations are making big data analytics a priority. Currently, more than a third of industries are currently using some form of advanced analytics on Big Data—for business intelligence, predictive analytics and data mining tasks, and this is expected to grow. Salaries for Analytics professionals are soaring. 

Learn more about Big Data Analytics through the following resources and information:

Transfer

Student Image

Potential Job Titles

Student Image
  • Business Intelligence Analyst 
  • Information Security Analyst
  • Data Warehousing Specialist

Salary Data

Information Security Analyst*
Average Wage: $42.96/hour

Business Intelligence Analyst**
Data Warehousing Specialist**

*Typically requires Bachelor's degree
** Emerging career specialty. Typically requires Bachelor's degree, please consult with program faculty for salary information. 

Information gathered pertains to seven county metro area - careerwise.mnscu.edu

Learning Outcomes

Applied Big Data Analytics - AAS 60 Credits

  • describe Big Data architecture
  • explain Big Data assets and map threats to Big Data assets.
  • install, configure and manage Hadoop platform.
  • create reports and charts with Big Data analytics platform.
  • implement analytics and data science projects using Splunk's statistics capability
  • perform searches and reports based on business analytics
  • use Splunk’s statistical functions to perform calculations on field values with conditional statements to generate security alerts
  • use Splunk's built-in and custom visualization capability to generate business intelligence
  • use Splunk’s Big Data to create interactive, real-time business dashboards that inform key business decisions.
  • analysis using Splunk's statistical functions such as min, max, mean, median and standard deviation.
  • use Splunk to deliver contextual security analytics in the form of interactive dashboards.
  • use DB Connect to explore configured SQL database schema with Big Data technology.
  • use Advanced Lookups to build a baseline lookup table and reference the baseline values in alert