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Center for Curriculum and Transfer Articulation
Foundations of Data Analytics and Programming
Course: CIS215

First Term: 2023 Fall
 Lec + Lab   3.0 Credit(s)   4.0 Period(s)   4.0 Load  
Subject Type: Occupational
Load Formula: T- Lab Load


Description: Overview of data analytics and programming, concepts, terminology, and how analytics and programming are used professionally in business. Use of office application software, dashboards and Integrated Development Environments (IDEs). Includes exploration of relevant emergent technologies.



MCCCD Official Course Competencies
1. Describe the history and terminology of data analytics and programming. (I)
2. Demonstrate understanding of the Extraction Transformation Load (ETL) process. (II)
3. Use spreadsheets for initial data analysis experience. (II, III, V, VI)
4. Describe different file types and sources of data. (III)
5. Use Relational Database Management Systems (RDBMS) to facilitate and mature enterprise use of data analytics. (IV, V)
6. Use prominent data visualization tools to analyze and visualize data. (V)
7. Use Integrated Development Environments (IDEs) to gain familiarity with leading languages used in data analytics, such as C# and Python programs. (VI)
MCCCD Official Course Competencies must be coordinated with the content outline so that each major point in the outline serves one or more competencies. MCCCD faculty retains authority in determining the pedagogical approach, methodology, content sequencing, and assessment metrics for student work. Please see individual course syllabi for additional information, including specific course requirements.
 
MCCCD Official Course Outline
I. Terminology
   A. Data analytics
      1. Value
      2. Varied
      3. Velocity
      4. Veracity
      5. Volatility
      6. Volume
      7. Vulnerability
   B. Data architecture
   C. Data dictionary
   D. Data governance
   E. Data management
   F. Data model
   G. Descriptive analytics
   H. Predictive analytics
   I. Data visualization
   J. Unified data architecture
   K. Unified data analytics
   L. Programming
      1. Data structures
      2. Object-oriented programming
      3. Validation
   M. Other terminology
II. Extraction Transformation Load (ETL) process
   A. Acquire data
      1. Importing data
      2. Exporting data
   B. Clean and transform data
   C. Analyze data
   D. Report data
III. File types and sources of data
   A. Structured data
   B. Unstructured data
IV. Database management systems
   A. SQL language
   B. NoSQL
   C. Database administration
      1. Software installation
      2. Software configuration
V. Dashboards/visualization
   A. Platforms
      1. Web
      2. Mobile
   B. Software use for data analysis
VI. Programming
   A. Integrated Development Environments (IDEs)
   B. Object-oriented programming languages
 
MCCCD Governing Board Approval Date: August 23, 2022

All information published is subject to change without notice. Every effort has been made to ensure the accuracy of information presented, but based on the dynamic nature of the curricular process, course and program information is subject to change in order to reflect the most current information available.