Data thinking

Data Thinking is a framework that integrates data science with the design process. It combines computational thinking, statistical thinking, and domain-specific knowledge to guide the development of data-driven solutions in product development. The framework is used to explore, design, develop, and validate solutions, with a focus on user experience and data analytics, including data collection and interpretation.

The framework aims to apply data literacy and inform decision-making through data-driven insights.

According to "Computational thinking in the era of data science":

Analyzing the broader digital strategy and assessing risks and opportunities is a common step before beginning a project. Techniques like coolhunting, trend analysis, and scenario planning can be used to assist with this.

In this phase, focus areas are identified, and use cases are developed by integrating organizational goals, user needs, and data requirements. Design thinking methods, such as personas and customer journey mapping, are applied.

A proof of concept is created to test feasibility and refine solutions through iterative evaluation to optimize for effective performance.

Solutions are tested and monitored for performance and continual improvement.

The following resources explain more about data thinking and its applications: