Introducing Cognitive AI Engine: Unleashing the power of intelligent insights.
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Data Observability
Introducing Rakuten SixthSense Data Observability, purpose-built to revolutionize the way you manage, monitor, and optimize your data pipelines. Say goodbye to data blind spots and hello to real-time insights and enhanced data accuracy.
Monitor, detect, analyze and prevent your data issues
Real-time data insights
Gain real-time visibility into your data pipelines with comprehensive monitoring and alerting capabilities. Be the first to detect anomalies, errors, and data quality issues instantly, ensuring your data is always reliable.
Avoid data downtime
Prevent future data incidents by understanding your most critical data assets and setting-up data quality rules and monitors for your assets at scale.
Faster root cause analysis
Enable your data teams with relevant metrics, traces and logs to quickly get to the root of the issue and understand its impacts, ensuring faster root cause analysis.
Enable data governance and compliance
Maintain compliance with industry standard regulations and assure superior data governance through automated data lineage, data quality rules and reliable reporting.
Data quality monitoring and predictive analytics
Continuously monitor data quality metrics at real-time, ensuring accurate and trustworthy data for decision-making.
Leverage advanced analytics and machine learning to anticipate potential data issues and proactively address them before they impact your business operations.
Alerting and notification
Receive real-time alerts and notifications for any data anomalies or discrepancies, allowing prompt action and inter-team collaboration.
Data lineage to trace issue genesis and impacts
Identify and trace the origins and transformations of your data to understand and act on potential upstream and downstream impacts in your end-to-end data system, enabling speedier root cause analysis and course correction.
Dashboards and visualizations
Visualize your organization’s data health through metrics and statistics around data quality, pipeline health and job performance.
Leverage actionable anomaly trends and data quality scores to optimize end-to-end data system operations, reducing MTTR and MTTD.