Data observability tools for Google Cloud SQL
Data observability tools help the company track and understand the state of its data at any given time and provide it with full insight into their data pipelines. They also allow them to identify, monitor and troubleshoot errors in order to minimize data issues and improve high data quality.
Monte Carlo
Monte Carlo's Data Observability platform uses machine learning to infer and learn what your data looks like, proactively identify data downtime, assess its impact, and notify those who need to know. It automatically and immediately identifies the root cause and lets you see all your data dependencies in one place, thereby allowing you to collaborate and resolve issues faster.
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Dataedo
Dataedo is a data governance & data catalog software with data observability features such as data lineage, data profiling, and schema change tracking.
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Datadog
Datadog is a unified observability platform that provides full visibility into the health and performance of each layer of your environment. It is an easy-to-navigate observability platform to explore and analyze your data, create and customize dashboards and other visualizations for data from across your systems, and leverage observability platform features like actionable alerts, threat detection rules, and the Datadog API. Overall, it brings together end-to-end traces, metrics, and logs to make your applications, infrastructure, and third-party services entirely observable.
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Instana
Instana's Enterprise Observability Platform ingests all performance metrics, traces all requests, and profiles every process, along with the capabilities needed to make observability work for the enterprise. Its automatic discovery, monitoring, root cause analysis, and feedback reduce the amount of stress when deploying new code or making changes to the system with immediate feedback on the performance and quality of your applications at each step of the software delivery pipeline.
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Data observability tools help the company track and understand the state of its data at any given time and provide it with full insight into their data pipelines. They also allow them to identify, monitor and troubleshoot errors in order to minimize data issues and improve high data quality.
By monitoring data across multi-layered IT architecture, data observability tools enable identifying bottlenecks and data issues no matter where they originate. Thanks to new insights into how the data is moving through your IT infrastructure, it's possible to improve identification and resolution of the errors and search for the issues that could potentially be missed.
To help you select the best solution for monitoring the data health in your company, we've prepared a list of data observability tools that will enable your team to understand your data systems to fix and prevent data problems.