These training slides introduce new researchers to the key principles that keep people’s information safe when working in the Eastern England Secure Data Environment (EE-SDE). They describe how, in certain circumstances, anonymised data could still carry a small risk of re-identification, particularly when datasets contain very small numbers or when multiple data points can be linked together. To prevent this, researchers learn about Standard Disclosure Control (SDC), a set of practical steps to check research outputs before anything is released outside the secure environment, ensuring that data remains protected and used responsibly. The training covers the main types of disclosure risk, such as small cell counts in tables, rare combinations of characteristics, or charts that show individual outliers. It also explains simple techniques researchers can use to reduce these risks, including grouping categories, suppressing small numbers, applying minimum thresholds, and rounding sensitive values. Researchers are introduced to tools like ACRO and SACRO-ML, which help automate parts of the checking process by flagging potential risks early and supporting safe model development. The slides also outline what information researchers must provide when preparing outputs for review, and how the airlock process ensures that every release is checked consistently. This presentation is accompanied by two python notebooks which provide example code for new users using ACRO and the SACRO-ML tools Together, the training provides researchers with the confidence and practical skills needed to produce safe, high-quality analysis while protecting the privacy of individuals whose data underpins their work.