Introduction to Big Data Analytics

Gain an overview of big data, the state of the prac­tice in ana­lyt­ics and the ana­lyt­ics life­cy­cle as an end-to-end process. Focus on the key roles of a suc­cess­ful ana­lyt­ic project. Top­ics may include: the main phas­es of the life­cy­cle; and devel­op­ing core deliv­er­ables to stakeholders.

Course at a glance
  • Aimed at mid-level management who are developing and implementing new business analytics within their organization.
  • In-class, face-to-face delivery.
  • Lecture and discussion-based course with class exercises and discussions of assigned readings.
  • Participants will be able to offer reflections of their personal experiences involving different management scenarios.
What you will learn

By the end of this course, you should be able to:

    • Distinguish attributes of big data analytics and identify elements of big data technology architecture.
    • Identify goals and critical success factors of a big data analytic project.
    • Recognize big data analytics deliverables.
    • Recognize drivers of big data analytics.
    • Identify attributes of data used in big data analytics.
    • Discuss requirements for succeeding with Analytics 3.0.
    • Discuss the role of Hadoop and MapReduce in Big Data.
    • Recognize key product capabilities of Big Data vendors.
    • Distinguish a big data analytics project from traditional projects.
    • Discuss the importance of change management in an analytics project.
    • Recognize the goal of data discovery and preparation and discuss the role of the Data Steward.
    • Describe the need for data cleaning and identify factors affecting methodology selection.
    • Differentiate amongst descriptive, diagnostic, predictive and prescriptive analytics.
    • Describe considerations and steps for selecting analytics software.
    • Describe the importance and approaches to calibrate models and data.
    • Identify key implementation planning elements.
    • Describe steps for model deployment.
    • Discuss the role of the automator.
    • Discuss the importance of model monitoring and maintenance.
    • Recognize components of a Model report.
    • Discuss steps to transition the project to operations.
This course has no prerequisites

Students from all educational backgrounds welcome. You can register for this course without applying and enrolling in a program.

Take note:

  • All reading materials will be available through eClass, the University of Alberta’s eLearning management tool.
When will
this course be offered?

New course schedules are released each June and November.

Course not yet scheduled

This course is not currently scheduled, but may be offered in an upcoming term.

New course schedules are announced each June and November.

Sign up for updates

Interested in future offerings of this course? We can let you know when this course becomes available.