New 2025 Gartner® Magic Quadrant™ for Augmented Data Quality Solutions - Download Report

Data Quality Monitoring and Incident Management with BigPanda


Overview

BigPanda is an event correlation and automation platform designed to streamline IT operations and incident management. By correlating and consolidating alerts from various sources, BigPanda helps teams quickly identify and resolve issues, reduce alert noise, and improve response times.

Integrating BigPanda with DQLabs enhances these capabilities by adding real-time data quality monitoring and observability. This integration ensures that the data driving BigPanda’s alerts is accurate, reliable, and actionable—enabling faster, more informed decision-making and reducing the risk of false positives or overlooked anomalies.

BigPanda Framework

The integration of DQLabs with BigPanda enhances IT operations by correlating data quality issues with system incidents, enabling faster root cause analysis and resolution. DQLabs continuously monitors data pipelines, detecting missing records, schema changes, and anomalies that could disrupt analytics and business operations. BigPanda’s AI-driven event correlation then maps these data quality alerts to relevant infrastructure and application incidents, reducing noise and preventing false alarms.

By linking operational failures with data health insights, IT teams can quickly identify whether an issue stems from system failures or bad data, avoiding prolonged troubleshooting. This proactive approach ensures reliable data for analytics, dashboards, and AI models, improving decision-making while minimizing downtime and operational risks.

Effective Data Quality Management with BigPanda

Automatically monitor data quality before alerts are sent to BigPanda, preventing data issues from escalating into operational incidents.

Correlate data quality metrics with operational events to provide context for faster incident resolution and informed decision-making.

By embedding data quality validation directly into the BigPanda workflow, ensure that only relevant and accurate alerts are triggered, reducing noise and improving response times.

Improve the effectiveness of automated IT workflows by ensuring that data is complete, accurate, and free from inconsistencies before it impacts incident management.

Detect and resolve data quality issues that could impact system performance, AI models, and analytics dashboards, ensuring continuous and reliable operations.

Enable a holistic view of both operational incidents and data health by integrating DQLabs’ data observability metrics with BigPanda’s infrastructure monitoring, providing end-to-end visibility.

Seamlessly Integrate with your
Modern Data Stack

DBT logo
Alation logo
Atlan logo
Talend logo
Google bigquery logo
Oracle logo
Databricks logo
Redshift spectrum logo
Azure synapse logo
Tableau logo
Redshift logo
PowerBI logo
MSSQL logo
Airflow logo
Amazon redshift logo
Snowflake logo
Collibra logo
denodo logo
Sap Hana logo
Jira logo
Amazon Athena logo
ADLS logo
ADF Pipeline logo
MS Teams logo
Slack logo
Amazon s3 logo
IBM DB2 logo
IBM DB2 Iseries logo
Azure Active Directory logo
Okta logo
Ping federate logo
Postgresql logo
IBM saml logo
Bigpanda logo
Amazon EMR logo

Getting Started with DQLabs is Fast and Seamless