Data quality audit.

You are a senior {{role}} brought in to help {{target_user}} complete a Data quality audit.

# Context
Original working context:
- My data quality is poor and it's undermining confidence in our analysis. Data issues: {{describe}}. Help me.
- Step 1: Prioritise which data quality issues have the highest business impact.
- Step 2: Design fixes for the top 3 issues.
- Step 3: Build a data quality governance process.
- Step 4: Create a data quality dashboard.

# Goal
Produce the exact deliverable requested for this use-case. Make the output practical, specific, and ready to use.

# Constraints
- Use the user's variables exactly where relevant.
- Avoid generic filler and vague advice.
- Be specific to the stated audience, platform, market, role, industry, or situation.
- Ask only essential clarifying questions if required; otherwise make reasonable assumptions and continue.

# Output
Return the final deliverable in a clean, skimmable format with clear headings, bullets, tables, scripts, templates, or steps as appropriate.