Comprehensive course analysis
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Who should attend
This seminar is for managers who want to effectively translate data analytics into business value, but do not necessarily have the technical expertise to do the analytics themselves.
About the course
The ability to use data to effectively drive decisions is an integral part of modern management. In this 2-day seminar, you will learn both the theoretical as well as practical applications of data analytics and how they apply to decision-making. You will deepen your understanding of descriptive, predictive and prescriptive analytics. Next, you will learn how to use that data to develop insights through a series of exercises and case studies. Finally, participants will gain a deeper understanding of how to make data driven business decisions within their organization. This course will enable you to be an informed and empowered manager of data, you will leave with a toolkit that allows you to make sense of data and how to make decisions using it.
Key Benefits & Takeaways
- Think critically about data
- Differentiate between good and bad data
- Avoiding data collection biases
- When to use descriptive, predictive or prescriptive analytics
- Understand different applications of business analytics across industries and sectors
- Identify opportunities for creating value using business analytics
- Properly structure data for your organization
Topics covered during the program
Using Data for Decision Making
- What is the role of data in decision making
- Discuss different frameworks to support decision-making in organizations
What is good data and how do you structure it
- Understand the perceived value of data
- 4 V’s of data: volume, velocity, variety and veracity
Making Well-Informed Decisions with AI
- What problems can AI help solve for your business?
- Impact on your operations, processes, employees, customers, and offerings
- Forecasting, sourcing, optimizing, automating, and enhancing user experiences
Bringing AI Into Your Organization
- When is the right time to bring in AI?
- Key elements of successful AI transformations
- AI readiness: changes to your processes, capabilities and culture
AI Execution: Your Business Case for Success
- Maximizing positive impact and mitigating risk of failure
- Building AI capacity – tools, consultants, internal teams
- Project scoping and infrastructure
Professor Ramaprasad joined the Smith School of Business as part of the DOIT area in Fall 2019. Prior to that she was an Associate Professor of Information Systems at the Desautels Faculty of Management at McGill University on Montreal, QC. She received her doctorate in Management, Information Sy...
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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.