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Data-driven Decision Making

This course is designed to be practical and applied, with a focus on real-world examples and case studies. Learners will ... Show more
Instructor
Blooms Academy
Category
This course will be available soon
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This course provides a practical and applied introduction to data-driven decision making, covering the skills and techniques needed to leverage data to inform business decisions. Learners will gain hands-on experience in framing business problems, exploring and analyzing data, building predictive models, and communicating insights to stakeholders.
 
It is designed to be practical and applied, with a focus on real-world examples and case studies. Learners will gain hands-on experience with data analysis and visualization tools, and develop the skills and confidence needed to drive data-driven decision making in their organizations.
 

Course Objectives:

  • Develop a data-driven mindset and approach to decision making.
  • Learn to frame business problems and identify key metrics and KPIs.
  • Apply data analysis and visualization techniques to generate insights.
  • Build predictive models to forecast outcomes and identify opportunitiesCommunicate data-driven insights and recommendations to stakeholders

Learning Outcomes:

  • Frame business problems and develop a data-driven approach to decision makingApply data analysis and visualization techniques to generate insights.
  • Build and interpret predictive models to inform business decisions.
  • Communicate data-driven insights and recommendations effectively to stakeholders.
  • Develop a data-driven decision framework to drive business outcomes
This course is designed to be practical and applied, with a focus on real-world examples and case studies. Learners will gain hands-on experience with data analysis and visualization tools, and develop the skills and confidence needed to drive data-driven decision making in their organizations.
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IMG-20250619-WA0004_2
Course details
Lectures 15
Assignments 1
Quizzes 5
Level Advanced
Intended audience
  • Business analysts and professionals.
  • Data analysts and scientists.
  • Managers and executives.
  • Anyone interested in leveraging data to inform business decisions

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