Making Evidence-Based Strategic Decisions

Drive alignment among managers, employees and the organizational goals through data analytics and data products. This course on digital transformation will show you how to turn your organization into a decision-making factory.

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What You Will 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

About This Course

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.

We will close out the course by examining two recent trends in data analytics. The first trend is the use of low-code/no-code tools by non-technical employees to create data applications. We will discuss best practices for creating low-code/no-code applications while providing a robust data infrastructure for the apps.

The second trend is the use of artificial intelligence (A.I.) and robotic process automation (RPA) in data analytics. We will examine the use of these tools, along with two of the most popular advanced data analysis tools: R and Microsoft's Power Platform.

This course is a high-level view of topics that we will explore in greater depth in the Architect certification portion of this program.

At A Glance

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Picture of Dr. Bill Brantley Your Instructor

Bill Brantley

My goal in teaching is not only to convey a body of knowledge but also help the student incorporate that knowledge into their careers and life. Teaching is not just about transmitting knowledge but also developing the student’s abilities as a critical thinker and an independent scholar.

Syllabus

Week 1
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 2
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 3
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 4
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

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