Making Evidence-Based Strategic Decisions from edX

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.

What's inside

Learning objectives

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

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

Syllabus

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

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Suitable for students in management or business analytics, as well as leadership

Appears to be a high-level overview of topics that will be covered in more depth in another part of this program, making it a good entry point for students new to data analytics

Features hands-on exercises, including practicums on low-code/no-code application building, which will help students gain practical experience

Covers data management, data science, and data analysis techniques that are fundamental to data analytics

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Making Evidence-Based Strategic Decisions with these activities:

Create a digital notebook and review course notes, assignments, and exams

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Reinforces key concepts and solidifies understanding by organizing and actively reviewing essential course materials.

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Create a digital notebook using a tool like OneNote or Notion.
Review lecture notes and make summaries or annotations.
Complete assignments and quizzes, reviewing them for areas of improvement.
Analyze past exams to identify strengths and weaknesses.

Read 'Designing Data-Intensive Applications'

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Sets a conceptual framework for data analytics and provides detailed insights into tools and concepts covered in the course.

View Secret Colors on Amazon

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Read Chapters 1 and 2 to understand the characteristics and challenges of designing data-intensive applications.
Read Chapters 3 and 4 to learn about data models, storage systems, and query languages.
Read Chapters 5 and 6 to explore data processing, system architecture, and data quality.

Practice using low-code/no-code tools to build data analytics applications

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Provides hands-on experience with the tools and techniques for building data analytics applications, enhancing practical skills.

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Select a low-code/no-code platform and complete their introductory tutorials.
Create a simple data analytics application that demonstrates key functionality.
Explore more advanced features and capabilities of the platform.

Three other activities

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Create a data dashboard to visualize and analyze data

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Develops practical skills in data visualization and analysis, enabling the effective communication of insights from data.

Browse courses on Data Visualization

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Choose a dataset and explore its contents.
Select appropriate charts and visualizations to represent the data.
Create an interactive data dashboard using a tool like Tableau or Power BI.

Write a blog post on decision-making in a digital enterprise

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Develops a deep understanding of the concepts and processes involved in effective decision-making within digital organizations.

Browse courses on Decision-Making

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Research the role of data in decision-making and the challenges faced by digital enterprises.
Outline the key principles and frameworks for effective decision-making.
Write the blog post, providing real-world examples and practical guidance.

Develop a data analytics solution for a real-world problem

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Applies the concepts and tools learned in the course to a practical project, fostering critical thinking and problem-solving abilities.

Browse courses on Data Analytics

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Identify a real-world problem that can be addressed using data analytics.
Gather and analyze data relevant to the problem.
Develop a data analytics solution and implement it using appropriate tools and technologies.
Evaluate the results of the solution and make recommendations.

Career center

Learners who complete Making Evidence-Based Strategic Decisions will develop knowledge and skills that may be useful to these careers:

Chief Data Scientist

Chief Data Scientists are responsible for leading data science teams and developing data science strategies within an organization. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better business decisions.

See salaries and explore the career path for Chief Data Scientist

Data Engineer

Data Engineers build and maintain the infrastructure that supports data analysis. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better decisions about data engineering.

See salaries and explore the career path for Data Engineer

Chief Data Officer

Chief Data Officers are responsible for overseeing the collection, analysis, and use of data within an organization. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better business decisions.

See salaries and explore the career path for Chief Data Officer

Data Science Manager

Data Science Managers oversee teams of data scientists and engineers. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better decisions about data science.

See salaries and explore the career path for Data Science Manager

Chief Analytics Officer

Chief Analytics Officers are responsible for overseeing the collection, analysis, and use of data within an organization. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better business decisions.

See salaries and explore the career path for Chief Analytics Officer

Director of Analytics

Directors of Analytics are responsible for developing and implementing data analytics strategies within an organization. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better business decisions.

See salaries and explore the career path for Director of Analytics

Vice President of Data Science

Vice Presidents of Data Science are responsible for leading data science teams and developing data science strategies within an organization. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better business decisions.

See salaries and explore the career path for Vice President of Data Science

Machine Learning Engineer

Machine Learning Engineers build and maintain the models that power machine learning applications. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better decisions about machine learning.

See salaries and explore the career path for Machine Learning Engineer

Data Architect

Data Architects design and build the systems that store and manage data. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better decisions about data architecture.

See salaries and explore the career path for Data Architect

Management Consultant

Management Consultants help businesses improve their performance. They use data analysis to help businesses make better decisions. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better business decisions.

See salaries and explore the career path for Management Consultant

Business Analyst

Business Analysts work with businesses to identify and solve problems. They use data analysis to help businesses make better decisions. This course may be useful by building a foundation in data analysis and decision-making. It can also help you understand how to use data to make better business decisions.

See salaries and explore the career path for Business Analyst

Market Researcher

Market Researchers conduct surveys, gather data, and analyze market trends to help businesses understand their customers. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better business decisions.

See salaries and explore the career path for Market Researcher

Product Manager

Product Managers are responsible for the development and launch of new products. They use data analysis to help make decisions about product design, marketing, and pricing. This course may be useful by helping you build a foundation in data analysis and decision-making. It can also help you understand how to use data to make better product decisions.

See salaries and explore the career path for Product Manager

Data Scientist

Data Scientists use their knowledge of math, statistics, and computing to extract meaningful insights from large amounts of data. This course may be useful by helping you build a foundation in data analysis and decision-making.

See salaries and explore the career path for Data Scientist

Data Analyst

Data Analysts use their programming skills to manipulate, interpret, and visualize data collected from various sources. This course may be useful by helping you build a foundation in data analysis and decision-making.

See salaries and explore the career path for Data Analyst

Making Evidence-Based Strategic Decisions

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