Strip out direct personal information such as names, addresses, and ID numbers from your dataset. Example: When presenting healthcare survey results, group ages into ranges (e.g., 30-40) and regions into broader areas instead of specific cities. Show data as averages, sums, or counts rather than individual records to prevent identification. Example: Display total sales per region instead of individual salesperson performance to maintain confidentiality. Remove confidential details or sensitive findings when presenting to a broader audience. Example: In an all-staff employee satisfaction survey presentation, focus on overall trends without revealing department-specific or manager-specific results.

When presenting statistical data, protecting privacy and confidentiality is essential. I ensure this by anonymizing data, either by removing personal identifiers or encrypting them to prevent any trace back to individuals. Another key strategy is using aggregate data, which helps avoid the risk of singling out or identifying any specific person. Additionally, I implement strict access controls, ensuring that only those who are authorized can view sensitive information. This combination of practices helps safeguard privacy without compromising the integrity of the data.

When presenting data, I keep privacy safe by removing personal details and showing only combined results, like averages or totals. For example, instead of showing a specific person's data, I share general trends. I also make sure to share the presentation securely with only the right people.