Overview
Data analysts use Glean’s MCP server to query structured data sources, combine quantitative and qualitative insights, and generate reports without switching between multiple analytics tools.Prerequisites
Recommended connectors:- Databricks (for data warehouse queries)
- Salesforce (for CRM data)
- Google Drive (for spreadsheets and reports)
- Confluence or Notion (for analysis documentation)
- Slack (for data discussions)
- Jira (for project tracking)
- Claude Desktop
- ChatGPT
- Cursor (for data notebooks)
- Any MCP-compatible interface
Use Cases
1. Natural Language Database Queries
Query structured data sources using natural language instead of SQL.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Translates natural language to SQL queries
- Executes queries against connected data warehouses
- Formats results for easy interpretation
- Identifies notable patterns or anomalies
2. Trend Analysis and Pattern Recognition
Identify trends in business metrics and customer behavior.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Queries time-series data
- Identifies patterns and correlations
- Combines quantitative data with qualitative context
- Provides business interpretation
3. Automated Report Generation
Generate recurring reports by pulling data from multiple sources.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Aggregates data from multiple sources
- Calculates key metrics automatically
- Adds qualitative context from discussions
- Formats for stakeholder consumption
4. Anomaly Detection in Financial Data
Identify unusual patterns or errors in financial datasets.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Analyzes financial data for outliers
- Identifies reconciliation issues
- Flags potential errors or fraud
- Prioritizes audit focus areas
5. Customer Cohort Analysis
Analyze customer behavior by cohort to understand retention and growth patterns.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Groups customers by cohort
- Calculates retention and lifetime value metrics
- Compares cohort performance
- Identifies successful acquisition strategies
6. Root Cause Analysis
Investigate data anomalies by combining quantitative and qualitative sources.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Combines quantitative metrics with qualitative context
- Correlates changes with events (deployments, campaigns)
- Searches for related discussions and issues
- Proposes hypotheses for investigation
7. Competitive Benchmarking
Analyze competitive data and market positioning.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Aggregates competitive intelligence
- Compiles market research and analysis
- Quantifies competitive performance
- Identifies positioning opportunities
8. Data Quality Assessment
Audit data quality and identify gaps or inconsistencies.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Identifies incomplete or inconsistent data
- Finds duplicates and errors
- Quantifies data quality issues
- Prioritizes remediation efforts
9. Predictive Analysis Support
Gather data and context for predictive modeling.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Aggregates historical data for modeling
- Surfaces domain knowledge from past analyses
- Suggests relevant features and variables
- Connects quantitative data with qualitative insights
10. Ad Hoc Business Questions
Answer urgent business questions quickly with data.Example Prompt
Example Prompt
Alternative Prompts
Alternative Prompts
- Quickly queries relevant data sources
- Provides evidence-based answers
- Combines data with contextual information
- Formats insights for executive consumption
Best Practices
Start with Clear Questions
Specify Time Ranges
Combine Quantitative and Qualitative
Validate Results
Document Assumptions
Troubleshooting
Can’t query structured data?- Verify Databricks Genie or similar connector is properly configured
- Check that your user has query permissions on the data warehouse
- Ensure the data source is actively indexed
- Be explicit about formulas: “Calculate as (new - old) / old * 100 for growth rate”
- Specify how to handle nulls, duplicates, or edge cases
- Ask Glean to show the query it’s using so you can verify
- Connect Slack channels where data discussions happen
- Index analysis documentation from Confluence or Notion
- Include links to past analyses and reports
- Check if time zones or date boundaries are defined consistently
- Verify filters and segments match your dashboard definitions
- Confirm you’re querying the same underlying data sources
Related Resources
- MCP Setup Guide - Initial configuration
- Chat Best Practices - Prompting tips
- Deep Research - In-depth analysis features