Full-stack visibility is key to understanding how data moves across your systems. With a data observability tool, you get data lineage tracking and metadata insights, which help you pinpoint bottlenecks, track dependencies, and ensure your data is accurate from source to destination.

The 'right to be forgotten' introduces several technical hurdles. For example, deleting user data across multiple systems, backups, and caches can be tricky. That's where data lineage tracking and pipeline orchestration visibility come in handy. They help you understand dependencies and ensure deletions are complete and safe without breaking downstream processes.

We’re just getting started! Soon, you’ll be able to monitor dbt run performance and resource utilization, define monitors in your dbt YAML files, and use custom metadata even more dynamically. These updates will further enhance your cloud data observability and make your workflows even more efficient.

Absolutely! With shared visibility into data flows and transformations, observability platforms foster better communication between data engineers, analysts, and business users. Everyone can see what's happening in the pipeline, which encourages ownership and teamwork around data reliability.

We built Sifflet to be your data stack's early warning system. Our observability platform offers automated data quality monitoring, anomaly detection, and root cause analysis, so you can identify and resolve issues before they impact your business. Whether you're scaling your pipelines or preparing for AI initiatives, we help you stay in control with confidence.

Absolutely! Flow Stopper supports integration with popular tools like Airflow for orchestration and Snowflake for storage. It can run anomaly detection and data validation rules mid-pipeline, helping ensure data quality as it moves through your stack.

Automated data lineage boosts data reliability by giving teams a clear, real-time view of data flows and dependencies. This visibility supports faster troubleshooting, better data governance, and improved SLA compliance, especially when combined with other observability tools in your stack.

Absolutely! While dbt tests are a great starting point, Sifflet takes things further with advanced observability tools. By ingesting dbt tests into Sifflet, you can apply powerful features like dynamic thresholding, real-time alerts, and incident response automation. It’s a big step up in data reliability and SLA compliance.