Business Intelligence

Design a dashboard for [purpose/audience]:

Purpose: [goal of dashboard]
Audience: [users and their needs]
Decisions supported: [what they'll do]
Data sources: [available data]
Update frequency: [real-time, daily, weekly]
Platform: [BI tool]

Dashboard design:
- Key questions dashboard answers
- Information hierarchy
- 5-8 primary metrics/KPIs
- Visualization type for each metric
- Filter and drill-down capabilities
- Layout and grouping
- Color scheme and design standards
- Interactivity elements
- Mobile responsiveness
- Performance optimization
- Default view
- Export capabilities
- User testing plan

Select the right metrics for [business objective]:

Objective: [what you want to achieve]
Stakeholders: [who will use metrics]
Current metrics: [existing measures]
Data availability: [what you can measure]
Decision frequency: [how often reviewed]

Metric framework:
- North Star metric
- Leading indicators (3-5)
- Lagging indicators (3-5)
- Input vs output metrics
- Counter-metrics (unintended consequences)
- Metric definitions (clear and unambiguous)
- Calculation methodology
- Target/threshold values
- Comparison periods
- Segmentation dimensions
- Ownership assignments
- Review cadence
- Metric hierarchy/relationship

Create a data story for [insight/finding]:

Finding: [key insight]
Data: [supporting evidence]
Audience: [decision makers]
Context: [business situation]
Desired outcome: [action you want]

Story structure:
- Compelling title
- Executive summary (3 sentences)
- Setup: Why this matters now
- Context: Current situation with data
- Conflict: Problem or opportunity revealed
- Resolution: Insight and recommendation
- Call-to-action: Specific next steps
- Supporting evidence
- Visualizations (specify types)
- Narrative flow
- Emotional connection
- Credibility elements
- Memorable conclusion

Design an executive report for [business area]:

Business area: [department/function]
Cadence: [weekly, monthly, quarterly]
Executive audience: [titles]
Decisions driven: [what they'll do with it]
Page limit: [constraint]

Report structure:
- Executive summary page
- Performance highlights (3-5 metrics)
- Trend analysis
- Performance vs targets
- Segment/category breakdown
- Key insights and interpretations
- Risks and opportunities
- Recommended actions
- Appendix with details
- Visual design approach
- Distribution method
- Supplementary data packet
- Review and approval process

Design a drill-down analysis for [metric]:

Metric: [top-level metric]
Anomaly/change: [what triggered analysis]
Available dimensions: [how you can slice data]
Business context: [relevant background]
Urgency: [timeline for analysis]

Drill-down approach:
- Analysis question hierarchy
- Dimension breakdown order
- Segmentation logic
- Comparative analysis points
- Statistical significance testing
- Root cause hypotheses
- Data exploration path
- Visualization sequence
- Pattern identification
- Outlier investigation
- Actionable insights
- Recommendations
- Further analysis needs
- Communication format

Recommend visualizations for [data/insight]:

Data type: [what you're showing]
Message: [key point to convey]
Audience: [technical level]
Context: [dashboard, report, presentation]
Complexity: [amount of data]

Visualization recommendations:
- Chart type selection and rationale
- Data encoding (color, size, position)
- Comparison facilitation
- Hierarchy and emphasis
- Color scheme (accessible)
- Annotation strategy
- Title and labels
- Legend placement
- Interactivity elements
- Common pitfalls to avoid
- Accessibility considerations
- Mobile adaptation
- Alternative views
- Tools/libraries to use

Plan a stakeholder presentation for [analysis/project]:

Topic: [what you're presenting]
Audience: [stakeholders and knowledge level]
Duration: [time available]
Goal: [decision/approval/information]
Complexity: [technical depth]

Presentation plan:
- Opening hook (first 30 seconds)
- Agenda and structure
- Context and why it matters
- Methodology (right amount of detail)
- Key findings (3-5 insights)
- Supporting evidence
- Implications and recommendations
- Q&A anticipation
- Slides sequence
- Visual emphasis points
- Pacing and timing
- Backup slides
- Handout materials
- Follow-up plan

Establish data governance for [BI program/initiative]:

Scope: [what data and systems]
Current state: [existing governance]
Challenges: [data quality, access, consistency]
Stakeholders: [data owners and users]
Compliance requirements: [regulations]

Governance framework:
- Data ownership model
- Data quality standards
- Data dictionary/catalog
- Naming conventions
- Metric definitions (single source of truth)
- Access and security policies
- Change management process
- Data lineage documentation
- Quality monitoring
- Issue resolution workflow
- Training and onboarding
- Governance committee structure
- Review and audit procedures
- Tool stack