Course description
Making Evidence-Based Strategic Decisions
What makes a good business decision?
How can we combine effective data analytics and feed robust foresight and scenario planning processes?
We need to rethink the organization, and see it as essentially a “decision factory.” Like a factory, employees at all levels make or contribute to decisions that, taken together, gives the organization the competitive edge in the marketplace. The news media is filled with stories of how a minor decision has major ramifications on the organization. In this course, we will learn how to train organizational members to effectively data products in their business decisions.
Digital organizations capture an enormous amount of data. Knowing how to mine and refine that data for strategic decision making effectively is what will separate the winners from the losers. As the business guru, Dr. Roger L. Martin, wrote in a 2013 Harvard Business Review article, knowledge workers turn the "raw material" of data into decisions. Decision-makers need the best data to make the best decisions.
This course will help your organization inventory the decisions its customers, employees, and leaders make and their data needs. We will discuss how to make good decisions and build quality data creation processes. You will also learn how to work with incomplete or ambiguous data and how to learn effectively from experience.
Upcoming start dates
Who should attend?
Prerequisites
None
Training content
Week One - Decision Factories
- Module One - Your Organization as a Decision Factory
- Module Two - What Kind of Decisions Do Your Customers Make?
- Module Three - What Kind of Decisions Do Your Employees Make?
- Module Four - What Kind of Decisions Do Your Leaders Make?
- Module Five - Porter's Five Forces Model and Your Decision Factory
Week Two - Data-Enabled Decision Making
- Module One - What is Good Decision Making?
- Module Two - Using Data in Making Decisions
- Module Three - What is Good Data?
- Module Four - Decision Making with Incomplete and Ambiguous Data
- Module Five - Learning from Experience
Week Three - Low-Code/No-Code Tools for Data Analytics Products
- Module One - The Low-Code/No-Code Revolution
- Module Two - Survey of Low-Code/No-Code Tools
- Module Three - Practicum: Building a Low-Code/No-Code Application (Part One)
- Module Four - Practicum: Building a Low-Code/No-Code Application (Part Two)
- Module Five - Building the Data Infrastructure for Low-Code/No-Code Applications
Week Four - Artificial Intelligence in Data Analytics
- Module One - How is A.I. used in Data Analytics
- Module Two - Big Data and Deep Learning
- Module Three - Robotic Process Automation
- Module Four - Data Analytics Software: R
- Module Five - Data Analytics Software: Microsoft Power Platform
Course delivery details
This course is offered through The University of Maryland, College Park, a partner institute of EdX.
2-3 hours per week
Costs
- Verified Track -$199
- Audit Track - Free
Certification / Credits
What you'll learn
- What makes a good business decision - foresight and scenario planning
- Why and how are digital enterprises decision factories?
- Training organizational members to effectively use the data products in their business decisions
- Using low-code/no-code tools in building data analytics products
- Using artificial intelligence tools in building data analytics projects
Contact this provider
edX
edX For Business helps leading companies upskill their labor forces by making the world’s greatest educational resources available to learners across a wide variety of in-demand fields. edX For Business delivers high-quality corporate eLearning to train and engage your employees...