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.

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Registration Information

CertificateLocationDateDelivery typeCostRegister
Business Analytics and Big Data in a Global EconomyPhoenix, AZTBDIn-person, Online$1,500Coming soon

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?

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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.

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Mid-level managers, business analysts, and other professionals who work with data and want to develop their teams' data literacy skills.

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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