Dynamic Search Interface with Elasticsearch and Automated Report Generation
Dynamic Search Interface with Elasticsearch and Automated Report Generation
šÆ 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: š Interactive web form for dynamic data querying ā” Real-time Elasticsearch data retrieval with complex filtering š Auto-generated reports (Text & CSV formats) with custom formatting š¾ Automatic file storage system for data persistence šÆ Configurable search parameters (amounts, time ranges, entity filters) š§ Scalable architecture for handling large datasets
š ļø 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%20Search%20Interface%20with%20Elasticsearch%20and%20Automated%20Report%20Generation/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 Create HTTP Basic Auth credentials in n8n Configure with your Elasticsearch username/password Assign to the "Search Elasticsearch" node
āļø Configuration
-
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
-
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
-
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
-
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
š How to use
For Administrators: Import this workflow template Configure Elasticsearch credentials Activate the workflow Share the webhook URL with data analysts
For Data Analysts: Access the search interface via the webhook URL Set parameters: Minimum amount, time range, entity filter Choose format: Text report or CSV export Submit form to generate instant data report 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
š 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:
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"
š§ 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
š·ļø Tags elasticsearch, data-search, reporting, analytics, automation, business-intelligence, data-processing, csv-export
š 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
ā ļø 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
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.
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