Business Analytics and Big Data in a Global Economy
Fees:
$1,500
Overview
In an era where data is likened to oil in terms of its value, business leaders must effectively harness this data to make informed decisions, drive innovation, and gain a competitive edge. Thunderbird School of Global Management’s Education Business Analytics and Big Data in a Global Economy program encapsulates the intersection of business, technology, and global insights under the current global knowledge economy we all live in. This two-day workshop will equip leaders with the skills and strategies to thrive in the data-driven global marketplace and emerge as data-savvy leaders poised to drive organizational success.
Registration Information
| Certificate | Location | Date | Delivery type | Cost | Register |
|---|---|---|---|---|---|
| Business Analytics and Big Data in a Global Economy | Phoenix, AZ | TBD | In-person, Online | $1,500 | TBD |
Key Benefits
- Enhance understanding of the current state and future potential of data analytics and big data.
- Develop hands-on experience in applying these concepts to real-world business challenges.
- Improve your ability to make informed decisions based on data insights.
- Gain competitive edge by leveraging data-driven strategies.
- Translate data insights into actionable business strategies.
- Develop leadership skills and mindset for success in the data-driven era.
- Convert data into compelling narratives that drive decision-making.
- Apply Generative AI techniques to enhance mathematical decision-modeling for complex business scenarios.
Who Should Attend?
C-suite executives, senior managers, and other decision-makers who need to understand and leverage the power of data to drive organizational success in a global context.
Mid-level managers, business analysts, and other professionals who work with data and want to develop their teams' data literacy skills.
Individuals seeking to advance their careers and become data-driven leaders in the global economy.
Topics
The program will use presentations, small group discussions, and interactive sessions to cover the following topics:
- Descriptive, predictive, and prescriptive analytics.
- Practical applications in text, video, image, and voice analytics.
- The Internet of Things (IoT), Artificial Intelligence (AI), data cybersecurity, and ethics in data.
- Web and sentiment analysis, text mining, and storytelling with data.
- Practical cases and discussions, creating models for complex business scenarios.
Faculty
