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.
Data quality is crucial for effective decision-making, operational efficiency, and regulatory compliance. It encompasses attributes like accuracy, completeness, consistency, and timeliness. Establishing a data quality framework involves defining goals, conducting inventory, implementing tools, and continuous monitoring. Regular auditing ensures sustained quality, helping organisations turn data quality into a strategic advantage.
The DASUD framework, developed by Nigel D'Souza, accelerates Data Governance implementation within 6 months by contextualising organisational needs. It focuses on designing data strategies through five key questions: Design, Acquire, Store, Use, and Delete. Prior prerequisites include defining roles, classification, approval processes, prioritising issues, and fostering a change-ready culture.
Success Resources is one of the best last minute decisions I have ever made! If anything I must thank Rob for telling me that there were still tickets available. Besides, their marketing wasn't that flash. Because when I read the ad, it said that the event was sold out. Turns out the cheapest rates were…
Nigel D'Souza 