Dynamic Search Interface with Elasticsearch and Automated Report Generation

🎯 What this workflow does

This template creates a comprehensive data search and reporting system that allows users to query large datasets through an intuitive web form interface. The system performs real-time searches against Elasticsearch, processes results, and automatically generates structured reports in multiple formats for data analysis and business intelligence.

Key Features:

• 🔍 Interactive web form for dynamic data querying
• ⚡ Real-time Elasticsearch data retrieval with complex filtering
• 📊 Auto-generated reports (Text & CSV formats) with custom formatting
• 💾 Automatic file storage system for data persistence
• 🎯 Configurable search parameters (amounts, time ranges, entity filters)
• 🔧 Scalable architecture for handling large datasets

🛠️ Setup requirements

Prerequisites

• Elasticsearch cluster running on https://localhost:9220
• Transaction dataset indexed in bank_transactions index
• Sample dataset: Download from Bank Transaction Dataset
• File system access to /tmp/ directory for report storage
• HTTP Basic Authentication credentials for Elasticsearch

Required Elasticsearch Index Structure

This template uses the Bank Transaction Dataset from GitHub: https://github.com/dataminexcode/n8n-workflow/blob/main/Dynamic Search Interface with Elasticsearch and Automated Report Generation/data

You can use this python script for importing the csv file into elasticsearch: Python script for importing data

Your bank_transactions index should contain documents with these fields:

{
  "transaction_id": "TXN_123456789",
  "customer_id": "CUST_000001", 
  "amount": 5000,
  "merchant_category": "grocery_net",
  "timestamp": "2025-08-10T15:30:00Z"
}

Dataset Info: This dataset contains realistic financial transaction data perfect for testing search algorithms and report generation, with over 1 million transaction records including various transaction patterns and data types.

Credentials Setup

1. Create HTTP Basic Auth credentials in n8n
2. Configure with your Elasticsearch username/password
3. Assign to the "Search Elasticsearch" node

⚙️ Configuration

1. Form Customization

• Webhook Path: Update the webhook ID if needed
• Form Fields: Modify amounts, time ranges, or add new filters
• Validation: Adjust required fields based on your needs

2. Elasticsearch Configuration

• URL: Change localhost:9220 to your ES cluster endpoint
• Index Name: Update bank_transactions to your index name
• Query Logic: Modify search criteria in "Build Search Query" node
• Result Limit: Adjust the size: 100 parameter for more/fewer results

3. File Storage

• Directory: Change /tmp/ to your preferred storage location
• Filename Pattern: Modify fraud_report_YYYY-MM-DD.{ext} format
• Permissions: Ensure n8n has write access to the target directory

4. Report Formatting

• CSV Headers: Customize column names in the Format Report node
• Text Layout: Modify the report template for your organization
• Data Fields: Add/remove transaction fields as needed

🚀 How to use

For Administrators:

1. Import this workflow template
2. Configure Elasticsearch credentials
3. Activate the workflow
4. Share the webhook URL with data analysts

For Data Analysts:

1. Access the search interface via the webhook URL
2. Set parameters: Minimum amount, time range, entity filter
3. Choose format: Text report or CSV export
4. Submit form to generate instant data report
5. Review results in the generated file

Sample Use Cases:

• Data analysis: Search for transactions > $10,000 in last 24 hours
• Entity investigation: Filter all activity for specific customer ID
• Pattern analysis: Quick analysis of transaction activity patterns
• Business reporting: Generate CSV exports for business intelligence
• Dataset testing: Perfect for testing with the transaction dataset

📊 Sample Output

Text Report Format:

DATA ANALYSIS REPORT
====================

Search Criteria:
- Minimum Amount: $10000
- Time Range: Last 24 Hours  
- Customer: All

Results: 3 transactions found

TRANSACTIONS:
=============

1. Transaction ID: TXN_123456789
   Customer: CUST_000001
   Amount: $15000
   Merchant: grocery_net
   Time: 2025-08-10T15:30:00Z

CSV Export Format:

Transaction_ID,Customer_ID,Amount,Merchant_Category,Timestamp
"TXN_123456789","CUST_000001",15000,"grocery_net","2025-08-10T15:30:00Z"

🔧 Customization ideas

Enhanced Analytics Features:

• Add data validation and quality checks
• Implement statistical analysis (averages, trends, patterns)
• Include data visualization charts and graphs
• Generate summary metrics and KPIs

Advanced Search Capabilities:

• Multi-field search with complex boolean logic
• Fuzzy search and text matching algorithms
• Date range filtering with custom periods
• Aggregation queries for data grouping

Integration Options:

• Email notifications: Alert teams of significant data findings
• Slack integration: Post analytics results to team channels
• Dashboard updates: Push metrics to business intelligence systems
• API endpoints: Expose search functionality as REST API

Report Enhancements:

• PDF generation: Create formatted PDF analytics reports
• Data visualization: Add charts, graphs, and trending analysis
• Executive summaries: Include key metrics and business insights
• Export formats: Support for Excel, JSON, and other data formats

🏷️ Tags

elasticsearch, data-search, reporting, analytics, automation, business-intelligence, data-processing, csv-export

📈 Use cases

• Business Intelligence: Organizations analyzing transaction patterns and trends
• E-commerce Analytics: Detecting payment patterns and customer behavior analysis
• Data Science: Real-time data exploration and pattern recognition systems
• Operations Teams: Automated reporting and data monitoring workflows
• Research & Development: Testing search algorithms and data processing techniques
• Training & Education: Learning Elasticsearch integration with realistic datasets
• Financial Technology: Transaction data analysis and business reporting systems

⚠️ Important notes

Security Considerations:

• Never expose Elasticsearch credentials in logs or form data
• Implement proper access controls for the webhook URL
• Consider encryption for sensitive data processing
• Regular audit of generated reports and access logs

Performance Tips:

• Index optimization improves search response times
• Consider pagination for large result sets
• Monitor Elasticsearch cluster performance under load
• Archive old reports to manage disk usage

Data Management:

• Ensure data retention policies align with business requirements
• Implement audit trails for all search operations
• Consider data privacy requirements when processing datasets
• Document all configuration changes for maintenance

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This template provides a production-ready data search and reporting system that can be easily customized for various data analysis needs. The modular design allows for incremental enhancements while maintaining core search and reporting functionality.