Balancing Analytics and data privacy works best when analyst looks into certain data interactions from a certain lens. - Ensure data policies are evaluated and clear guidelines are set - Ensure relevant stakeholders are clear on information that can be shared and the ones that is sensitive is kept confidential -Providing actionable insights without compromising on sensitive customer information needs to be worked upon at all times as an analyst.

When handling sensitive customer behavior data, balancing transparency and confidentiality is crucial. I always begin by reviewing our data policy to make sure everything stays within legal and ethical boundaries. It's important to set clear expectations right away, so I explain what can and can’t be shared due to privacy regulations. When possible, I offer aggregated data—giving clients valuable insights without exposing individual customer information. This way, we build trust while keeping privacy intact.

Clear boundaries are established about what can be shared, based on privacy laws and ethical standards. I also focus on offering aggregated data, which provides valuable insights without revealing individual details. This approach allows me to maintain transparency while safeguarding confidentiality.

When handling sensitive customer behavior data, I prioritize transparency and data privacy. I ensure clients understand our strict compliance with GDPR and LGPD regulations, emphasizing that data access is granted only when it aligns with these laws. I anonymize and aggregate data to protect individual identities before sharing any insights, ensuring privacy is never compromised. Additionally, I set clear guidelines and agreements on data usage, maintaining regular audits to ensure all access requests are justified and secure. This approach builds trust with clients while safeguarding customer data, balancing the need for insights with ethical data management.

Champion the customer and protect their privacy. Offer solutions that can mask customer PII with encryption or anonymisation techniques. Ensure all parties clearly understand the risks involved and get the client to sign off the requests and acknowledge the risks if they are on the higher side of the spectrum.