8: How-to Guides
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      How to Create Scheduled Workflows That Read from Linked Tables

      Scheduled workflows in Rayven.io allow you to automatically run logic at specific times — hourly, daily, weekly, etc.

      Combining this with linked tables (Primary and Secondary), you can build powerful automations that analyze related datasets, send reports, trigger alerts, or update records without manual input.

      This is ideal for recurring processes that depend on relational data, like compliance checks, operational summaries, or status reports.


      Use Cases

      • Daily check for devices overdue for maintenance by comparing logs to a device list.

      • Weekly summary report that pulls from both equipment metadata and performance readings.

      • Scheduled email that notifies stakeholders if any linked data flags an exception.

      • Nightly sync job that pulls from tables and pushes to an external API.

      How It Works

      Rayven’s Workflow Builder lets you schedule a workflow using a Scheduler Node, which triggers the logic at a defined interval. You can then:

      • Pull from your Primary Table (e.g. Devices)

      • Use a Linked Table Node or Table Join to bring in Secondary Table data

      • Apply logic and conditions

      • Output results to notifications, dashboards, APIs, or data stores

      Step-by-Step Instructions

      Step 1: Start a New Workflow

      1. Go to your project → Workflow Builder.

      2. Click + Create Workflow and give it a name.

      Step 2: Add a Scheduler Node

      1. Drag in the Scheduler Trigger node.

      2. Set your schedule:

        • Hourly, Daily, Weekly, Custom Cron

        • Choose timezone and start time

      Step 3: Read From Primary Table

      1. Add a Table Data Node.

      2. Select your Primary Table (e.g., Devices).

      3. Optionally add filters (e.g., only active devices).

      Step 4: Link a Secondary Table

      1. Add another Table Data Node (your Secondary Table, e.g., Maintenance Logs).

      2. Use a Join Field (e.g., device_id) to relate it back to the primary table.

      3. Filter or sort the linked data as needed (e.g., last_maintenance_date < today - 30).

      🔍 Optional: Use a Merge Node to combine data into a single structure for downstream use.

      Step 5: Add Workflow Logic

      • Use Condition Nodes to apply logic (e.g., "If last maintenance > 30 days").

      • Branch logic or tag exceptions.

      Step 6: Add Output Actions

      Examples:

      • 📧 Email Node → Send summary to a team.

      • 🧠 AI Agent → Generate a report from combined data.

      • 📄 PDF Generator → Create a formatted report.

      • 🌐 API Call Node → Push result to another system.

      Step 7: Save & Test

      1. Save the workflow.

      2. Use the manual preview to simulate a scheduled run.

      3. Validate output with logs and make prompt/payload adjustments as needed.

      Best Practices

      • Use descriptive field names to avoid confusion between tables.

      • Keep your joins lightweight — don’t over-fetch secondary data unless needed.

      • For large datasets, consider batching to reduce processing time.

      • Always test the workflow with different types of data (including no-match scenarios).

      • Log outcomes to a monitoring table for auditing or dashboard display.

      Examples

      Schedule Primary Table Linked Table Outcome
      Daily at 6 AM Devices Maintenance Logs Email alert if device overdue
      Every Monday Machines Performance Stats Weekly report PDF
      Nightly Locations Sensor Events Push flagged events to API

      Troubleshooting

      • Workflow runs but no data?
        Check filters in table nodes and ensure records match the join field.

      • Duplicate records?
        Use group-by or deduplication logic after joining tables.

      • Workflow not triggering?
        Confirm your scheduler is active and cron/timezone is set correctly.

      Next Steps

      👉 How to Link Tables in a Workflow
      👉 How to Generate Reports from Workflows
      👉 Using AI Agents in Scheduled Workflows
      👉 Monitoring and Logging Workflow Runs