Who should attend
Students from all educational backgrounds welcome. You can register for this course without applying and enrolling in a program.
About the course
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.
All reading materials will be available through eClass, the University of Alberta’s eLearning management tool.
David has been an associate with Performance Group since 2011. He is an accomplished program and project manager with key strengths in organizational alignment, operations and performance planning and management and quality improvement. He has extensive experience with core services reviews, orga...
Videos and materials
Read more about Business Analytics
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.