The exponential growth of data flows in the past few years created the need to come up with new, automated solutions to deal with data problems. One of the most crucial challenges data teams face today is ensuring quality and reliability when dealing with complex and high volumes of data. Having the right tools is key to facing these challenges.
Similar to the challenges software engineers faced a decade ago amid the introduction of cloud infrastructure, the data world is now building tools for integration, automated testing, and observability to reduce complexity.
dbt - the go-to tool for data transformation
Dbt makes the process of transforming data faster and more reliable by combining modular SQL with best practices from the software engineering world. This tool makes data engineering activities accessible to a wider range of roles within the organization, allowing data consumers to own the entire analytics engineering workflow. By helping companies become more data-driven, dbt has quickly become the go-to tool for data teams that are increasingly relying on this tool for their data modeling and transformation.
Sifflet + dbt Core for Faster, Stronger, Better Data Products
Sifflet is thrilled to announce its latest full integration with dbt Core. This integration will help data teams ensure that data is reliable at each stage of their data pipelines through Sifflet’s full data stack data observability platform, and enhance the monitoring coverage by involving business data consumers and supporting advanced use cases.
Data teams relying on dbt will be able to:
Want to learn more about our latest integration with dbt? Reach out for a demo.
Know when data breaks and fix it efficiently by leveraging Sifflet’s end-to-end lineage and automated monitoring and anomaly detection. Read more on how our product works.
