Building on Days 6-7: Take your AI feature and design its data strategy using the three pillars framework.

Task 1: Data Acquisition Plan and Privacy Impact Assessment (5 min)

Open your Gemini chat. Update your Master Prompt:

Task 2: Quality Safeguards (5 min)

Review the output of your prompt. Having understood data privacy risks, now think about data quality risks: what is the consequence if the data is flawed? Think of 3 data quality risks for your feature and note them down. For example, a risk of "Incomplete user profiles" could be mitigated with "Default values for missing fields, flag low-confidence predictions".

Now go back to Gemini, and prompt it to identify the top 3 data quality risks for the feature, alongside strategies for mitigation. Compare this to your own thinking - did any of the same risks come up?