A blog about Product Management, Data Management and Self-Driven Learning
The post discusses the importance of quality data in AI product management, outlining the DASUD model: Design, Acquire, Store, Use, and Delete. It emphasises defining success, collecting accurate data, securely storing it, ethical use, and timely deletion. Trust in data is crucial for effective AI implementation, ensuring good governance.
As a volunteer at Product Camp, I decided to put together this handy little guide for Attending your first Product Camp unconference can be exciting yet nerve-wracking. Embrace the spontaneity, stay open to new experiences, and engage with participants using personal questions. Remember everyone shares similar feelings, so network freely and have fun. Prepare with essentials like water and comfy shoes to enhance your experience.
Free apps often seem costless, but they exploit personal data as their main revenue source. Users unknowingly grant access to sensitive information, which can be sold or used for targeted advertising. To safeguard privacy, it's crucial to review app permissions, read privacy policies, and choose privacy-focused alternatives.
Public Wi-Fi is convenient but poses significant security risks, including Man-in-the-Middle attacks, fake hotspots, and unencrypted networks. To enhance safety, users should employ VPNs, avoid sensitive activities, verify network legitimacy, and enable two-factor authentication. Staying informed and adopting security measures can help protect personal data while using public Wi-Fi.
Smart devices enhance daily convenience but raise significant privacy concerns. They often collect extensive data through microphones and cameras, leading to risks like eavesdropping and hacking. Users should review privacy settings, secure devices, and understand manufacturers' data practices. Legislation like GDPR and CCPA aims to improve data control and transparency.
Nigel D'Souza 