Computer Information Systems

Data Analytics - CCL

Effective term: 
2017 Fall
Final term: 
2018 Fall
Total credits required: 

The Certificate of Completion (CCL) in Data Analytics program is designed to prepare students to model, synthesize, analyze, and present large data sets for business decision making. Courses will focus on the techniques and computer software used in industry to extract data from various data sources, model and integrate that data, and then visualize this data for business decision making and intelligence gathering.

Suggested Course Plan Sequenced by Semester

Program notes

Students must earn a grade of "C" or better in all courses within the program.

++ indicates any suffixed courses.

Admission criteria

Students must have satisfactory score on the District math placement test.

CIS105Survey of Computer Information Systems (3) OR
CIS114DEExcel Spreadsheet (3) 3
CIS117DMMicrosoft Access: Database Management 3
CIS214DEAdvanced Excel Spreadsheet: Level II 3
CIS217AMAdvanced Microsoft Access: Database Management (3) OR
CIS276++Any Database Management Systems courses (3) 3
GBS151Introduction to Business 3
GBS220Quantitative Methods in Business (3) OR
GBS221Business Statistics (3) 3
  1. Demonstrate a working knowledge of computer information systems, fundamental computer concepts, and programming techniques. (CIS105)
  2. Use a computer spreadsheet program to create, store, modify, and print electronic spreadsheets. (CIS114DE, CIS214DE)
  3. Demonstrate the skills needed to set up, maintain, and use a database management program. (CIS117DM)
  4. Design and create database structures to store, retrieve, update, and display data in a relational database using SQL. (CIS217AM, CIS276++)
  5. Identify the fundamental characteristics and functions of modern business, including business principles, marketing, labor relations, and business risk. (GBS151)
  6. Solve probability applications. (GBS220)
  7. Distinguish between continuous and discrete variables. (GBS220)
  8. Find probabilities for normal random variables by using the standard normal distribution. (GBS220)
  9. Describe the normal distribution and its characteristics. (GBS220)
  10. Calculate and interpret the measures of central tendency for either raw or grouped data. (GBS221)
  11. Use statistical inference techniques and confidence levels for decision making when testing hypotheses. (GBS221)
  12. Use regression and correlation analysis, and interpret the results of the analysis. (GBS221)