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Business Intelligence and Data Analytics

  • Description
  • Knowledge & Skills
  • Curriculum
  • Textbooks/Manuals
  • Teaching & Evaluation

Course work provides an introduction data analytics and how to use them in a intelligent way in a business. Learn to apply data analytics skills to the area of business intelligence (BI). Focus is placed on the components of business intelligence project lifecycle such as the importance of big data, real life industry examples, technologies within big data, information management, business analytics, and data privacy.


  • Know the importance of communication within Business Intelligence and Data Analytics
  • Know how to work with imperfect data to find the perfect solution
  • Know the ethical strategies to manage conflicts in diverse environments

Core Competency:   Ability to enhance and build business intelligence capabilities by adapting the appropriate technology and software solutions

  1. Apply principle and techniques of database design, administration, and implementation to enhance data collection capabilities and decision-support systems
  2. Critique the role of information and analytics in supporting business processes and functions
  3. Access business intelligence architecture and implement activities that improve decision making skills

Core Competency:  Analyze ethical principles applied to contexts and environments of data privacy

  1. Evaluate the moral challenges involving the best practise of ethical behaviour
  2. Access the cause of conflict that comes off in organizational settings and apply ethical strategies to manage conflicts in diverse environments
  3. Describe the cost and benefit that is created from relationships within the ethics of data privacy



Adapt technology and software solutions to build business intelligence capabilities

  • Be able to freely work with Hadoop File System, Schema, and Parallel Computing Framework
  • Ability to understand the role of people in the equation of business intelligence

Core Competency: Ability to commutate effectively in a variety of contexts from the course

  1. Articulate assumptions, analyses, and interpretations of data in an oral format
  2. Identify and articulate the major theories and principles of ethics
  3. Effectively communicate analytical conclusions in written and visual formats

Core Competency: Design tested and effective advanced analytics models and simulations for decision making

  1. Organize big data sets into meaningful structures, incorporating data profiling and quality standards
  2. Incorporate the data analysis framework for optimal performance
  3. Perform a needs assessment and analytical problem framing

Course Content

1. Introduction (5 Hours)
2. Industry Examples of Big Data (18 Hours)
3. Big Data Technology (10 Hours)
4. Information Management (8 Hours)
5. Business Analytics (8 Hours)
6. The People Part of the Equation (12 Hours)
7. Data Privacy Ethics (10 Hours)

Michael Minelli, Michele Chambers, & Ambiga Dhiraj, Big Data, Big Analytics: Emerging Business Intelligence and Analytic Trends for Today's Businesses (2012)

Method of Evaluation 

Type Number % value
  Team Project  1  20%
  Tests  2  30%
  Weekly Discussions  10  10%
  Graded Homework  15  15%
  Final Examination  1  25%

Teaching Method 

Method Number of Hours
  Lecture  35
  Seminar  15
  Supervised Lab  25

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