Data-Driven Decision Making (DDDM) Micro-Credential Course

Data is transforming how governments, businesses, civil society organisations, and researchers understand challenges, design interventions, and evaluate outcomes. Across sectors, evidence-based decision-making is increasingly becoming essential for solving complex public and organisational problems.

However, while access to data has grown significantly, many professionals still lack the practical skills needed to interpret data, generate meaningful insights, and translate evidence into informed action. Traditional data courses often focus heavily on technical tools, leaving learners without a structured understanding of how data supports decision-making in real-world contexts.

To address this need, CivicDataLab developed the Data-Driven Decision Making (DDDM) Course with partners to equip learners with practical skills to analyse data, generate insights, and support evidence-based decision-making across diverse professional contexts.

Designed for learners with little or no technical background, the course combines interactive learning modules, real-world case studies, collaborative exercises, and guided assessments to build confidence in working with data. Participants learn not only how to analyse information but also how to critically interpret findings, communicate evidence effectively, and apply data responsibly in decision-making processes.

Over 30 hours of self-paced online learning, the course introduces the complete decision-making workflow, from understanding data and assessing its quality to analysing trends, building visualisations, generating recommendations, and evaluating outcomes.

The curriculum covers:

• Foundations of Data-Driven Decision Making, including data types, sources, quality assessment, and limitations.
• Descriptive analytics, data cleaning, statistical reasoning, and identifying bias in datasets.
• Practical Exploratory Data Analysis (EDA) using Excel and AI-assisted analytical tools.
• Designing interactive dashboards and effective data visualisations using open-source platforms.
• Translating analysis into actionable insights, recommendations, and evidence-informed decisions while integrating Monitoring, Evaluation, and Learning (MEL) approaches.
• Responsible data use, including ethics, privacy, governance, AI, and understanding how bias and governance choices influence analytical outcomes.

Upon successful completion, learners earn a recognised micro-credential demonstrating practical competency in data-driven decision-making.

The course is ideal for students and early-career professionals, researchers and development practitioners, government officials and civil society professionals, and anyone with basic familiarity with data seeking to strengthen practical data literacy. No prior experience in coding, statistics, or data science is required.