DataMonkey: Unlocking Actionable Insights from Raw Data

Automate Reporting Fast with DataMonkey Tutorials

What it is

A concise tutorial series that shows how to use DataMonkey to build, schedule, and deliver automated reports from raw data to stakeholders with minimal manual work.

Who it’s for

• Business analysts who prepare recurring reports
• Data engineers automating ETL and report pipelines
• Product managers needing regular metrics
• Small teams without dedicated BI staff

Key learning outcomes

• Connect DataMonkey to common data sources (CSV, databases, APIs)
• Create repeatable data transformation workflows
• Build templated report layouts (tables, charts, summaries)
• Schedule automated report generation and delivery (email, Slack, S3)
• Monitor and troubleshoot failed runs

Tutorial outline

1. Quick start (10–20 min): Connect a CSV and generate a basic report.
2. Transformations: Filter, aggregate, join, and pivot data visually or with scripts.
3. Visuals & templates: Create charts, reusable templates, and conditional formatting.
4. Scheduling & delivery: Set up cron-like schedules and delivery channels (email/Slack/S3).
5. Testing & alerts: Add test data checks, logging, and alerting for failures.
6. Scaling: Best practices for large datasets, parallel runs, and incremental updates.

Tools & integrations covered

• Data sources: PostgreSQL, MySQL, Google Sheets, CSV, REST APIs
• Outputs: PDF/Excel reports, HTML dashboards, Slack messages, cloud storage
• Automation: Built-in schedulers, webhooks, and CI/CD integration

Expected time to proficiency

• Basic automated reports: 1–2 hours
• Robust pipelines with monitoring: 1–2 days

Next steps (recommended)

• Follow the Quick start and complete the Scheduling & delivery lesson.
• Apply to a real recurring report in your organization within 48 hours.