Analytics is typically undertaken for a variety of reasons. The most basic and common use is to understand what is currently happening. Counts of things e.g.; how many product A units were sold in EMEA region. The second reason is correlation and control. Typical in this space are concepts like averages and variance. Finally, there is the concept of predictive analytics. Analytics must enable oversight and management and where appropriate diagnostics and root cause identification.
The student will understand the impact of data quality on analytics. The student will understand data management concepts and have an overview of the more common approaches and issues encountered in preparing data for analytics.
The student will have a basic understanding of statistics, correlation and pattern recognition that enables prediction. Further the student will use probability to guide interpretation of analytics.
Students must attend at least 80% of classes to graduate with either the Diploma or Certificate of Attendance unless a serious and verifiable reason for further absence is provided.
If completing the course online, attendance and participation is tracked through Moodle.
A pass grade on the written assignment will be required for awarding of the Diploma.
This course will be assessed through continuous assessment.