Business & Entrepreneurship Data Analytics

Data-Driven Decision Making

Turn raw data into clear, defensible business decisions with practical frameworks, metrics, and analysis.

Data-Driven Decision Making logo
Quick Course Facts
15
Self-paced, Online, Lessons
15
Videos and/or Narrated Presentations
4.9
Approximate Hours of Course Media
About the Data-Driven Decision Making Course

Data-Driven Decision Making helps you make clearer, more confident choices by using evidence instead of guesswork. This practical course is ideal for professionals who want to strengthen their Business Strategy, evaluate information more effectively, and turn analysis into action that improves outcomes.

Build Smarter Business Strategy With Data-Driven Decision Making

  • Learn how to frame the right business question before looking at data
  • Use practical frameworks to assess data quality, relevance, and risk
  • Compare options with simple analytical methods you can apply immediately
  • Communicate insights clearly so stakeholders can act with confidence

Turn raw data into clear, defensible business decisions with practical frameworks, metrics, and analysis.

This Data-Driven Decision Making course takes you through the full decision process, from defining a problem to presenting recommendations that support better Business Strategy. You will explore where data comes from, how to judge whether it is trustworthy, and how to choose metrics that actually matter for the decision at hand.

As you progress, you will learn how to summarise information, compare options, and interpret the difference between correlation, causation, and confounding. The course also covers experiments, A/B testing, forecasts, and common statistical traps, helping you avoid mistakes that can weaken decision quality.

Beyond analysis, you will practice balancing data with experience and context, which is essential in real-world leadership and team settings. You will also develop skills in storytelling and stakeholder communication so your findings are understood and supported across the organisation.

By the end of the course, you will have a structured decision framework you can use with your team, along with the confidence to make better choices under uncertainty. You will finish able to turn raw data into clear, defensible business decisions with practical frameworks, metrics, and analysis.

Course Lessons

Full lesson breakdown

Lessons are organized by topic area and each includes descriptive copy for search visibility and student clarity.

Foundations

1 lesson

This lesson introduces evidence-based decision making as a practical discipline: defining a decision, identifying the evidence needed, and separating signal from noise. Learners will see how data supp…

Problem Definition

1 lesson

In this lesson, you’ll learn how to turn a vague business issue into a clear, decision-ready question. Strong problem definition is the foundation of data-driven decision making: it focuses the team, …

Data Sources

1 lesson

This lesson introduces the major types of data used in business decisions and explains where that data comes from . Learners will distinguish between qualitative and quantitative data, primary and sec…

Data Evaluation

1 lesson

This lesson shows how to judge whether a dataset is actually fit for a decision. Learners will examine accuracy, completeness, consistency, timeliness, and relevance, then use a practical checklist to…

Measurement

1 lesson

Good decisions start with the right metric , not more metrics. In this lesson, learners will see how to choose measures that reflect the business outcome they want to improve, avoid vanity metrics tha…

Summarising Information

1 lesson

Descriptive analysis is the foundation of decision making because it turns raw data into a clear picture of what is happening. In this lesson, learners focus on summarising information with the right …

Decision Comparison

1 lesson

Comparing options is where analysis becomes decision support. In this lesson, learners use simple, practical methods to compare alternatives without overcomplicating the process. We focus on side-by-s…

Interpretation

1 lesson

This lesson helps learners separate association from cause and effect so they can make better business decisions. It explains why two metrics can move together without one causing the other, how confo…

Testing

1 lesson

Experiments and A/B tests can be powerful ways to reduce guesswork, but only when they are designed and interpreted responsibly. In this lesson, you will learn how to define a clear hypothesis, choose…

Planning Ahead

1 lesson

Forecasts and predictions help you plan ahead, but only when you understand what they can and cannot tell you. In this lesson, you will learn how to read a forecast, check its assumptions, compare sce…

Critical Thinking

1 lesson

This lesson helps learners spot the most common biases and statistical traps that distort business decisions. It focuses on practical warning signs in dashboards, reports, and team discussions, so you…

Judgement

1 lesson

This lesson explains how to combine data with professional judgment so decisions are not driven by numbers alone or by intuition alone. Learners will see when data is strong enough to lead, when conte…

Storytelling

1 lesson

Stakeholders rarely act on data alone; they act on clear, relevant, and credible insight . In this lesson, you will learn how to translate analysis into a message that fits the audience, supports a de…

Applied Practice

1 lesson

This lesson focuses on how to make strong decisions when the data is incomplete, noisy, or conflicting. You will learn a practical process for defining the decision, estimating uncertainty, comparing …

Implementation

1 lesson

In this lesson, you will build a practical decision framework your team can use consistently when choices have real business consequences. The goal is not to replace judgment with formulas, but to mak…

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About Your Instructor
Professor Christina Ross

Professor Christina Ross

Professor Christina Ross guides this AI-built Virversity course with a clear, practical teaching style.