InputDCS

InputDCS Node Documentation

Overview

The InputDCS node connects your workflow to data stored in your organization's database systems. This node retrieves information from database tables and makes it available to other nodes in your workflow, enabling data-driven automation and AI processing.

Think of this node as your workflow's data gateway - it pulls customer records, transaction data, inventory information, or any other business data from your databases so your automation can work with real, up-to-date information.

When to Use This Node

Use the InputDCS node when you need to:

• Pull customer information for personalized communications
• Retrieve order data for processing workflows
• Access inventory levels for stock management automation
• Get employee records for HR workflows
• Fetch any business data stored in your company databases

Configuration Parameters

Database Selection

Database

• Field Name: selectedSystemId
• Type: Dropdown menu
• Default Value: None selected
• Simple Description: Choose which database system contains the data you need
• When to Change This: Select the database that contains your target information (customer database, inventory system, etc.)
• Business Impact: This determines which data source your workflow can access

Table

• Field Name: selectedDataFrameId
• Type: Dropdown menu with search capability
• Default Value: None selected
• Simple Description: Choose the specific table within your selected database
• When to Change This: Pick the table containing the exact data you need (customers, orders, products, etc.)
• Business Impact: This determines which specific dataset your workflow will process

Column Configuration

Column Purpose Settings

• Field Name: columnDef
• Type: Data grid with dropdown selections for each column
• Available Options:
  • Input: Use this column's data as input for AI processing or workflow logic
  • Predict: This column contains values you want to predict or analyze
  • Ignore: Skip this column entirely in your workflow
• Simple Description: Define how each database column should be used in your workflow
• When to Change This: Customize based on what data you need - mark customer names as "Input" for personalization, sales amounts as "Predict" for forecasting
• Business Impact: Proper column configuration ensures your workflow processes only relevant data, improving performance and accuracy

Data Filtering and Sorting

Filter

• Field Name: paramFilter
• Type: Text field
• Default Value: Empty (no filtering)
• Simple Description: Add conditions to limit which records are retrieved from your database
• When to Change This: Use filters to get specific data like "customers from last 30 days" or "orders over $100"
• Business Impact: Filtering reduces processing time and focuses your workflow on relevant data only

Limit

• Field Name: paramLimit
• Type: Number input with spin buttons
• Default Value: 0 (no limit)
• Simple Description: Set the maximum number of records to retrieve from the database
• When to Change This: Use limits for testing (try 10-50 records first) or when you only need recent data
• Business Impact: Limiting records prevents overwhelming your workflow and reduces processing costs

Sort

• Field Name: paramSortedBy
• Type: Text field
• Default Value: Empty (database default order)
• Simple Description: Specify how to order the retrieved records
• When to Change This: Sort by date for chronological processing, by amount for priority handling, or by customer name for organized output
• Business Impact: Proper sorting ensures your workflow processes data in the most logical business order

Advanced Settings

Disable Cache

• Field Name: disableCache
• Type: Toggle switch (On/Off)
• Default Value: Off (cache enabled)
• Toggle States:
  • Off (Cache Enabled): Stores retrieved data temporarily for faster repeated access
  • On (Cache Disabled): Always fetches fresh data directly from the database
• When to Change This: Enable when you need real-time data that changes frequently, like live inventory levels
• Business Impact: Disabling cache ensures data freshness but may increase processing time and costs for large datasets

Manual Order

• Field Name: manualOrderId
• Type: Number input with spin buttons
• Default Value: 1
• Valid Range: 1 and higher
• Simple Description: Controls the processing sequence when multiple InputDCS nodes exist in your workflow
• When to Change This: Set different numbers (1, 2, 3) when you have multiple database inputs that must be processed in a specific order
• Business Impact: Proper ordering prevents data conflicts and ensures logical workflow execution

Step-by-Step Configuration

Setting Up Your Database Connection

1. Add the Node

   • Drag the InputDCS node from the left panel onto your workflow canvas
   • Connect it to your starting node or place it where you need data input

2. Select Your Database

   • Click on the InputDCS node to open the configuration panel
   • Choose your database from the "Database" dropdown menu
   • If you don't see your database, contact your IT administrator

3. Choose Your Data Table

   • After selecting a database, the "Table" dropdown will populate with available tables
   • Select the table containing your target data
   • Use the search function if you have many tables

4. Configure Column Usage

   • Review the column list that appears
   • For each column, select its purpose from the dropdown:
     • Choose "Input" for data you want to use in your workflow
     • Choose "Predict" for values you want to analyze or forecast
     • Choose "Ignore" for columns you don't need

Setting Up Data Filtering (Optional)

5. Add Filters

   • In the "Filter" field, enter conditions to limit your data
   • Example: "created_date > '2024-01-01'" for recent records only
   • Leave empty to retrieve all records

6. Set Record Limits

   • Enter a number in the "Limit" field to cap how many records to retrieve
   • Start with small numbers (10-50) for testing
   • Use 0 for no limit (retrieve all matching records)

7. Configure Sorting

   • In the "Sort" field, specify how to order your data
   • Example: "created_date DESC" for newest records first
   • Leave empty for database default ordering

Advanced Configuration

8. Cache Settings

   • Leave "Disable Cache" turned off for better performance
   • Turn on only if you need real-time data that changes constantly

9. Processing Order

   • Set "Manual Order" to 1 for your first database input
   • Use higher numbers (2, 3, etc.) if you have multiple InputDCS nodes

10. Test Your Configuration

    • Click "Test Configuration" to verify your setup
    • Review the sample data to ensure it matches your expectations
    • Save your configuration when satisfied

Real-World Use Cases

Customer Service Automation

Business Situation: A support team wants to automatically pull customer account information when processing service requests.

What You'll Configure:

• Select "CustomerDatabase" from the database dropdown
• Choose "customer_accounts" from the table dropdown
• Set customer name and email columns to "Input"
• Set account status column to "Input"
• Add filter: "status = 'active'"
• Set limit to 1000 for manageable processing

What Happens: When a service request comes in, the workflow automatically retrieves relevant customer data, enabling personalized and informed responses.

Business Value: Reduces response time by 60% and improves customer satisfaction through personalized service.

Sales Lead Processing

Business Situation: A sales team needs to automatically process and prioritize new leads based on company size and industry.

What You'll Configure:

• Select "LeadsDatabase" from the database dropdown
• Choose "prospect_companies" from the table dropdown
• Set company name and industry to "Input"
• Set employee count to "Input" for prioritization
• Set revenue potential to "Predict" for forecasting
• Add filter: "lead_date > '2024-01-01'"
• Sort by "employee_count DESC" to prioritize larger companies

What Happens: The workflow retrieves lead information and automatically prioritizes prospects based on size and potential value.

Business Value: Increases sales team efficiency by 40% and improves lead conversion rates through better prioritization.

Inventory Management

Business Situation: A retail company wants to automatically reorder products when stock levels fall below minimum thresholds.

What You'll Configure:

• Select "InventorySystem" from the database dropdown
• Choose "product_stock" from the table dropdown
• Set product name and current stock to "Input"
• Set minimum threshold to "Input"
• Add filter: "current_stock < minimum_threshold"
• Sort by "last_updated DESC" for most recent data
• Enable "Disable Cache" for real-time stock levels

What Happens: The workflow continuously monitors inventory levels and triggers reorder processes when stock runs low.

Business Value: Prevents stockouts, reduces manual monitoring by 80%, and optimizes inventory costs.

Industry Applications

Healthcare Organizations

Common Challenge: Medical practices need to access patient records for appointment scheduling and treatment planning, but manual data retrieval is time-consuming and error-prone.

How This Node Helps: Automatically retrieves patient information, medical history, and appointment data from healthcare management systems.

Configuration Recommendations:

• Select your patient management database
• Choose patient records table
• Set patient ID and contact information to "Input"
• Set medical history fields to "Input" for treatment context
• Use filters for specific date ranges or conditions
• Enable cache disable for real-time patient status

Results: Healthcare providers save 25 hours per week on data retrieval and reduce patient record errors by 90%.

Financial Services

Common Challenge: Banks and financial institutions need to analyze customer transaction patterns for fraud detection and personalized service offerings.

How This Node Helps: Pulls transaction data, account information, and customer profiles from banking systems for automated analysis.

Configuration Recommendations:

• Connect to your core banking database
• Select transaction history tables
• Set transaction amounts and dates to "Predict" for pattern analysis
• Set customer demographics to "Input" for personalization
• Use date filters for recent transaction analysis
• Sort by transaction date for chronological processing

Results: Financial institutions detect fraud 75% faster and increase cross-selling success by 45% through better customer insights.

E-commerce Platforms

Common Challenge: Online retailers struggle to personalize customer experiences and manage inventory across multiple sales channels.

How This Node Helps: Retrieves customer purchase history, product data, and inventory levels for personalized recommendations and stock management.

Configuration Recommendations:

• Connect to your e-commerce database
• Select customer orders and product tables
• Set purchase history to "Input" for recommendation engines
• Set inventory levels to "Input" for availability checks
• Filter for active customers and available products
• Sort by purchase date for recent activity focus

Results: E-commerce businesses see 35% increase in repeat purchases and 50% reduction in inventory management time.

Troubleshooting Common Issues

No Tables Appear After Selecting Database

Problem: The table dropdown remains empty after selecting a database. Solution:

• Verify you have access permissions to the selected database
• Contact your database administrator to confirm table availability
• Try refreshing the node configuration by clicking away and back

Column Configuration Not Saving

Problem: Column purpose settings reset when you close the configuration panel. Solution:

• Ensure you click "Save" after making column changes
• Verify your workflow has been saved to preserve node settings
• Check that you have edit permissions for the workflow

Data Retrieval Takes Too Long

Problem: The node times out or takes excessive time to retrieve data. Solution:

• Add filters to reduce the amount of data being retrieved
• Set a reasonable limit (start with 100-500 records)
• Enable caching for frequently accessed data
• Consider breaking large datasets into smaller, filtered chunks

Retrieved Data Doesn't Match Expectations

Problem: The data pulled by the node doesn't contain what you expected. Solution:

• Review your filter conditions for accuracy
• Check column configurations to ensure relevant fields are set to "Input"
• Verify you selected the correct table from the dropdown
• Test with a small limit first to examine sample data

Best Practices

Performance Optimization

• Start with small data limits during testing and gradually increase
• Use specific filters to retrieve only necessary data
• Enable caching for stable data that doesn't change frequently
• Sort data appropriately to get the most relevant records first

Data Security

• Only retrieve columns you actually need for your workflow
• Use filters to limit access to sensitive information
• Regularly review and update access permissions
• Consider data retention policies for cached information

Workflow Design

• Place InputDCS nodes early in your workflow to provide data for subsequent processing
• Use multiple InputDCS nodes with different manual order settings when you need data from multiple sources
• Test thoroughly with sample data before processing large datasets
• Document your filter and sort logic for future maintenance

The InputDCS node is your gateway to leveraging existing business data in automated workflows. Proper configuration ensures efficient, secure, and reliable data access that powers intelligent business automation.