The work of Data Analytics Units varies from one organization to another, but it typically centers on a set of integrated tasks that collectively form the organization’s data lifecycle:
Understanding the Need Listening to decision-makers and identifying the real question behind each request, as the apparent request—such as creating a chart—often reflects a deeper need, such as identifying where a problem is concentrated. | Data Collection and Integration Accessing data across different systems and integrating it into a unified, usable form instead of leaving it in isolated systems that do not communicate with one another. |
Data Quality Management Ensuring that data is complete, accurate, consistent, up to date, and free of duplicates. Any analysis based on poor-quality data will produce misleading results, regardless of how well it is performed. | Developing Performance Indicators Translating objectives and questions into measurable performance indicators based on standardized definitions agreed upon by all stakeholders, ensuring that the same figure is not presented in different ways. |
Analysis and Insight Generation Answering three key questions: What happened? Why did it happen? What does it mean for us? A figure alone is not sufficient unless it is understood within its context and properly interpreted. | Reporting and Data Visualization Designing dashboards and reports that communicate the message within seconds while minimizing the reader’s cognitive effort. The goal is clarity, not decoration. |