Data Analytics

Data Analytics - CCL

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.

Program Code

5884 Certificate of Completion (CCL) in Data Analytics  

Other Degree Options

The Certificate of Completion (CCL) in Database Development prepares students to design and implement the infrastructure for business solutions using database and programming tools. The Certificate focuses on administrative tasks and building database applications using programming skills such as data collection, query techniques and database creation.

Course Format

Classes are offered in a variety of formats: in-person, online, hybrid, day, evening, full-time and part-time.  

How long will it take?

It takes a minimum of 1 year as a full-time student. This estimate does not include developmental education courses (courses under 100 level).

Textbooks

Many CIS classes use low or no-cost textbooks. General Education courses may have textbooks that cost more.

Program Curriculum Requirements (18 credits)

Suggested Course Sequence

Semester 1

  • CIS114DE Excel Spreadsheet (3)
  • CIS117DM Microsoft Access: Database Management (3)
  • GBS151 Introduction to Business (3)
  • Total Credits: 9

Semester 2

  • CIS214DE Advanced Excel Spreadsheet: Level II (3)
  • CIS276DA MySQL Database OR CIS276DB SQL Server Database (3)
  • GBS220 Quantitative Methods in Business OR GBS221 Business Statistics (3)
  • Total Credits: 9

MCCCD Program and Award Information
Major: 
5884
Effective term: 
2019 Spring
Final term: 
9999
Award: 
CCL
Total credits required: 
18
CIP Code: 
52.1301
Description

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.

Award notes

Students must earn a grade of C or better in all courses within the program.
Effective Spring 2019, the Computer Information System (CIS) courses required by this program are not applicable if taken more than eight (8) years prior to the completion of the program of study. Consult with an Academic Advisor for complete information.

Admission criteria

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

Required courses
Course #Course TitleCredits
Credits:18
CIS114DEExcel Spreadsheet3
CIS117DMMicrosoft Access: Database Management3
CIS214DEAdvanced Excel Spreadsheet: Level II3
 
CIS217AMAdvanced Microsoft Access: Database Management (3) OR
CIS276++Any Database Management Systems courses (3)3
 
GBS151Introduction to Business3
 
GBS220Quantitative Methods in Business (3) OR
GBS221Business Statistics (3)3
Competencies
  • Use a computer spreadsheet program to create, store, modify, and print electronic spreadsheets. (CIS114DE, CIS214DE)
  • Demonstrate the skills needed to set up, maintain, and use a database management program. (CIS117DM)
  • Design and create database structures to store, retrieve, update, and display data in a relational database using SQL. (CIS217AM, CIS276++)
  • Identify the fundamental characteristics and functions of modern business, including business principles, marketing, labor relations, and business risk. (GBS151)
  • Solve probability applications. (GBS220)
  • Distinguish between continuous and discrete variables. (GBS220)
  • Find probabilities for normal random variables by using the standard normal distribution. (GBS220)
  • Describe the normal distribution and its characteristics. (GBS220)
  • Calculate and interpret the measures of central tendency for either raw or grouped data. (GBS221)
  • Use statistical inference techniques and confidence levels for decision making when testing hypotheses. (GBS221)
  • Use regression and correlation analysis, and interpret the results of the analysis. (GBS221)