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.
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.
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.
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.
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.
This step involves retrieving the object comparison list, which helps in identifying schema differences between versions, aiding in the deployment process.
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.
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.
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.
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.
In most organizations, there are multiple systems that consume the same data. Therefore, it is a continuous challenge to keep data in-sync across systems. 4DAlert’s flexible architecture allows it to connect diverse source systems and check key data points across the systems.
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