Instill confidence in data and your team and Guarantee successful data deliveries.
4DAlert monitors data in your target platform and proactively compares metrics, identifies issues, missing values, or column level quality issues in target data set from specific data sources, and alerts data anomalies before end users find them or its downstream systems and consumers.
AI and ML to learn patterns and adjust alert criteria for Anomaly detection
4DAlert LEVERAGES AI AND ML TO LEARN FROM PAST DATA POINTS AND ALERTS WHEN FIND ANOMALIES
AI and ML-based algorithms learn from patterns, detect anomalies, and alert data owners when anomalies are detected within data sets, a process that helps build end-user confidence in data in your warehouse and saves time for end-users to reconcile data and take a wrong decision on bad data.
CERTIFY DATA IN BUSINESS INTELLIGENCE SYSTEMS
NOTIFY USERS PRO-ACTIVELY WHEN DATA IS WRONG
TAKE PRO-ACTIVE ACTION TO CORRECT DATA BEFORE END USERS TELL YOU TO DO SO
SAVE END USERS AND SUPPORT TEAM'S TIME BY RECONCILING DATA ALL THE TIME
Certify data in business intelligence systems
What Good is an Analytics Platform If Users Can’t Trust the Data?
Business users use insights from analytics platforms to take key decisions that are in many ways consequential for an organization’s goal and overall performance. Therefore, it is very important that data is accurate and reconciled and has passed basic checks. Automated reconciliation algorithms embedded into the 4DAlert solution help to validate and confirm that data pass basic checks regularly – a process that builds trust and confidence in data in the analytics platform.
Notify users early when data is wrong
Just being reactive is not enough, needs to be proactive.
4DAlert helps the analytics team to tackle data issues more proactively than reactively. The solution scans data sets in source systems, compares that with data in analytics platforms, and detects an anomaly. As and when anomalies are found, the solution alerts key stakeholders responsible for the data set and helps them tackle the issue before users identify the issue. The ability to notify users and take corrective action before end-users tell you to do so helps you increase trust in your analytics platform.