Lecture, seminar and hands-on exercises in the lab
- Introduction to Big Data Analytics
- Data Analytics Lifecycle
- Data Mining Process
- Review Basic Data Analytics Methods and planning data analytic steps
- Business Intelligence Trends and Big Data Trends
- Make use of MS Excel pivot tables for analytics
- Exploring the use of one of the data analytics tools – Tableau among many out there
- Advanced Analytics – Technology and Tools
- Database Analytics using Tableau
- Decision Analysis through designing visualizations
- Explain foundations of Big Data Analytics & Data Mining Process
- Describe modern approach to Business Intelligence / Data Analytics
- Analyse Business Intelligence Trends & Trends in Big Data
- Utilize effective ways to analyze data
- Develop data analytics plan
- Use data analytic tools such as Tableau
- Explore Advanced Analytics – Technology and Tools.
- Explain philosophies, tools and techniques of decision analysis in terms of data management and data visualization.
|Participation||0% - 5%|
|Assignments/Project:||15% - 25%|
|Quizzes (Minimum 2) *||10% - 20%|
|Midterm exam *||20% - 30%|
|Final Exam *||25% - 35%|
# Some of the assessments may involve group work.
*In order to pass the course, students must, in addition to receiving an overall course grade of 50%, also achieve a grade of at least 50% on the combined weighted examination components (including quizzes, tests, exams).
No Text Required, Notes to be provided by Instructor
EMC Education Services. Data Science & Big Data Analytics - Latest Ed., Wiley
Tableau documentation / guides.
Courses listed here must be completed either prior to or simultaneously with this course:
- No corequisite courses
Courses listed here are equivalent to this course and cannot be taken for further credit:
- No equivalency courses