Use Cases
Real workflows for different roles and teams using MarcoPolo.
MarcoPolo is built for workflows that require correlating data across disparate systems. The teams using it tend to fall into a few categories:
RevOps and Sales Ops correlate Salesforce records with data warehouse tables to generate pipeline metrics, track deal velocity, and build board-ready reports. See Cross-Source Analysis and Reporting.
Data Engineering profiles datasets, automates weekly query runs against Snowflake or BigQuery, builds and tests ETL pipelines, and validates data quality. See Data Exploration, Pipelines, and Data Quality.
Infrastructure and Development traces production issues across S3 logs and relational databases in a single conversation. Best experienced in Claude Code with the MarcoPolo plugin. See Triage & Break-Fix.
Manufacturing and QC runs yield analysis and failure mode paretos across distributed data stores like Microsoft Fabric. See Data Exploration and Reporting.
Customer Success cross-references support tickets with CRM data to identify account health patterns before renewal cycles. See Cross-Source Analysis.
Detailed walkthroughs
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Data Exploration & Profiling: Get oriented in unfamiliar data sources. Profile datasets, map relationships, and document what you find in RULES.md.
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Cross-Source Analysis: Correlate data across systems that don't normally talk to each other. Query each source, join locally in DuckDB.
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Business Intelligence & Reporting: Build dashboards, track KPIs, and automate recurring reports.
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Triage & Break-Fix: Investigate production issues by checking logs, querying databases, and tracing data through systems. The plugin is recommended for this workflow.
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Data Quality & Validation: Check for anomalies, validate completeness, reconcile data across sources.
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Pipeline Building & ETL: Build, test, and debug data pipelines. Transform and move data between systems.