Data Observability Insights

With Data Observability Insights, data teams can access the synthesized metadata Monte Carlo generates to build dashboards, analyze data platform team performance and even commit to and track SLAs. This level of detail, common in software engineering and DevOps tooling, makes it possible for data teams to understand what data matters most to the business based on usage, access, and data quality checks. Additionally, Insights makes it easy to create and share high-level reporting with CTOs and CDOs, fostering great data trust and ownership across the company. Sample Tables: - Detailed data incident data for the trailing 90 days - List of key tables based on recent usage - Recurring queries with deteriorating performance in the past 30 days - And more. Fields included: - Incident type - Incident identification time - Resolution time - Expected threshold - Actual value that resulted in anomaly - Number of users with queries executed on the table - Number of read and write queries executed Expected Workflow: Data Insights is quickly and easily turned on with the help of your Monte Carlo customer success team. You can email your customer success rep directly or email [e-mail]

搜集汇总

背景与挑战

背景概述

Data Observability Insights 数据集通过合成元数据，帮助数据团队构建仪表板、分析平台性能并跟踪服务等级协议，从而识别业务关键数据。它包含90天内的事件详情、关键表列表和性能查询等字段，如事件类型和查询数量，并可通过客户支持快速启用工作流程。