Ascend for Databricks Data Pipelines
Accelerate the Power of the Databricks Lakehouse
With the unprecedented automation of Ascend, data engineers and analytics engineers share one single pane of glass for Databricks data pipelines—and program their transformation logic via a complete SDK as well as an intuitive visual interface.
Get More Out of Databricks ELT with Ascend Data Automation
With our potent self-orchestrating control plane, put data Databricks to work and multiply the effectiveness of your data team.
Increase Engineering Velocity
Dramatically improve time to value in building and launching Databricks ELT pipelines to deliver data products in minutes:
- Focus on the business logic of your Databricks data pipelines.
- Let the Ascend platform automate the common orchestration chores.
- Collaborate seamlessly across teams and with stakeholders.
Deliver Quality Data
Reduce risk and improve data quality in the Databricks lakehouse with:
- Actionable in-line data validation rules
- Native notifications
- Rich exception handling features
Streamline data maintenance with:
- Automated incremental loading
- Data profiling
- Intelligent partitioning
Guarantee Data Lineage
Assure unbreakable lineage from data sources through all Databricks data pipelines without additional tooling. Trace the end-to-end integrity of all data and code dependencies linked through Ascend’s unprecedented DataAware™ control plane in real-time, regardless of scale.
- Iterate and tune individual Databricks data pipeline hotspots with Ascend’s visual tools, built in metrics, and clean CI/CD integration. As a result, obtain rapid problem resolution and reduced running costs throughout the data pipeline lifecycle.
- Reduce seams in your data stack with Ascend’s integrated access, monitoring, credential management.
- Maintain clean separation of complex workflows while encouraging collaboration with powerful data pipeline sharing features.