Modern Data Analytics Simplified

Transform Your Data Landscape with 4DAlert's Unified Solution

Transform your data with 4DAlert's Generative AI-powered MDM platform. Automating Data Reconciliation and validating millions of entries daily, we ensure top Data quality and real-time Observability with AI/ML. With integrated CI/CD schema comparison, Automatic Change Management, and ER Diagram generation, 4DAlert makes enterprise data management seamless and scalable.

Our Global Clients

Our Solutions

How We Can Help You

GenAI based Master Data Management (MDM)

  • Match & Merge
  • Survivorship
  • Rebuilt Content for SAP & Salesforce
  • Generative AI-Based MDM

Automated Data Reconciliation

  • Connects Multiple Sources
  • Eliminates Mismatches
  • Regular Validation Checks
  • Supports Complex Data Pipelines

Proactive Data Quality Management

  • ETL Testing Automation
  • Data Accuracy Maintenance
  • Validation Workflows
  • Trust Frameworks

End-to-End Data Observability

  • Pipeline Monitoring
  • Anomaly Detection
  • Error Resolution
  • Performance Insights

CI/CD Pipeline Automation

  • Automated Deployments
  • Integration with DevOps Tools
  • Pipeline Failure Prevention
  • Version Control Synchronization

Schema Comparison & Automatic Change Deployment

  • Schema Comparison Tools
  • Automated Change Deployment
  • Database Synchronization
  • Deployment Risk Mitigation

Your Data, Our Solution – In a Snapshot

4DAlert's Gen AI-based MDM dashboard showcasing match & merge for multi-domain records, survivorship logic for prioritizing sources, pre-built SAP and Salesforce integration, and AI-powered automated data management to enhance data quality.

Gen AI-based Master Data Management

4DAlert enhances MDM with Match & Merge to connect multi-domain records, eliminate duplicates, and ensure accuracy. Its Survivorship logic prioritizes the most reliable source for master records. Pre-built Content for SAP & Salesforce ensures seamless integration across key platforms. Generative AI-Based MDM enables smarter, automated data management, improving data quality over time.

Automated Data Reconciliation & Accuracy

4DAlert automates the reconciliation of data between your analytics platform and source systems after every data load. By using AI/ML-powered algorithms, it ensures data accuracy and detects discrepancies before they impact decision-making. This proactive approach allows you to identify and resolve data issues early, preventing problems from reaching your users.

4DAlert's automated data reconciliation dashboard: AI/ML-powered algorithms ensuring accuracy between analytics platforms and source systems, identifying discrepancies, and resolving issues proactively to maintain data integrity.
4DAlert's data quality monitoring dashboard with AI-driven observability, detecting anomalies, generating adaptive rules, and ensuring consistent and actionable insights across all platforms.

Data Quality Monitoring & Observability

With 4DAlert’s data observability module, you can continuously monitor the health of your data across all platforms. Using machine learning, it automatically detects anomalies, generates adaptive rules, and identifies the root causes of issues. This helps you prevent data quality problems before they arise, ensuring reliable, actionable data for your teams.

CI/CD Automation & Schema Consistency

4DAlert automates CI/CD pipelines, Schema comparison, and Change deployment to maintain consistent, compliant, and error-free data environments. It seamlessly synchronizes database schemas, minimizing deployment errors and accelerating rollouts. With built-in compliance checks and version control, 4DAlert ensures regulatory adherence while maintaining a complete history of schema changes, reducing manual intervention and ensuring systems remain secure and up-to-date.

4DAlert automates CI/CD pipelines, synchronizes database schemas, ensures error-free deployments, integrates compliance checks, and maintains version control for secure, consistent, and up-to-date environments.

Our Approach In Data Reconciliation

Automated Source-to-Target Data Reconciliation

Data from multiple sources often mismatches between source and target. 4DAlert connects diverse data sources, using its AI/ML engine to automatically reconcile data and alert stakeholders via email, texts, and Slack.

4DAlert's automated source-to-target reconciliation: integrates multiple sources like Snowflake, Redshift, and Databricks, detects discrepancies using AI/ML, and sends real-time alerts to maintain data accuracy and consistency.

Automated Data Reconciliation within Target with Historical Trend

When connecting to source systems isn't possible due to restrictions or rigidity, 4DAlert’s AI engine uses historical trends to detect data anomalies and reconciliation issues in new data.

4DAlert's automated reconciliation leveraging historical data trends to identify anomalies and ensure accuracy when direct source system access is unavailable.

Automated Source-to-Target Data Reconciliation

Data from multiple sources often mismatches between source and target. 4DAlert connects diverse data sources, using its AI/ML engine to automatically reconcile data and alert stakeholders via email, texts, and Slack.

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Our Approach In CI/CD Process

Retrieve Object Comparison List to Identify Schema Differences

This step involves retrieving the object comparison list, which helps in identifying schema differences between versions, aiding in the deployment process.

 

Push DDL Changes to Source Control

In this step, the changes made to the Data Definition Language (DDL) are pushed to source control, ensuring that all modifications are properly tracked and versioned.

Generate DDL for Schema Deployment

Execute Data Definition Language (DDL) to Apply Schema Changes.

 

Execute Data Definition Language (DDL) to Apply Schema Changes

The final step involves executing the generated DDL to apply the necessary schema changes, completing the automated pipeline process.

 

Our Technologies

Connect and Unify your Metadata effortlessly with pre-built connectors.

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