Ascend.io, the leader in data pipeline automation, is announcing a new integration with dbt, the pioneer of analytics engineering, that addresses the need for a third-party orchestration tool for dbt models. Ascend for dbt not only offers advanced orchestration capabilities without additional overhead, it also eases the pain of operationalizing dbt models with optimization as a core focus.
Many analytics engineering teams leverage dbt Core to effectively build data pipelines for their organization. However, these same engineers, when moving to operationalize these pipelines, are met with challenges in speed, cost, and efficiency.
Ascend for dbt steps in to solve this engineering burden, offering pipeline operations, automation, and optimization technology that empowers data teams to deliver products faster and with greater efficiency, according to the company. With intelligent execution—a process of limiting unnecessary data processing—Ascend for dbt allows engineers to build with dbt Core while deploying their models to Ascend with efficiency at the forefront.
“Our center of gravity tends to be around the operational part of data engineering and data pipelines,” said Sean Knapp, founder and CEO of Ascend.io. “And so, in many ways, it [the dbt integration] helps to combine the best of both worlds, taking the operational side and the optimizations technology of Ascend and how we orchestrate and optimize these pipelines—which just wasn't quite there in the existing dbt ecosystem.”
Ascend’s intelligent orchestration offers a variety of capabilities for optimizing and automating data pipeline orchestration, including:
- Greater understanding between the code and the data
- Automatic lineage tracking across multiple dbt projects
- Automation controller for advanced control over pipeline changes, including auto-generated jobs to operate a network of pipelines
- Reduced cloud bills and engineering operation costs with dynamic intelligence
These features culminate in an integration that alleviates the burdens of data engineering while driving truly efficient pipeline operations.
“Data and analytics engineering teams are going to be very excited about the automation factor, because oftentimes, they're the ones who are being pushed to better operationalize and better optimize those pipelines. And having to do that by hand is risky, cumbersome, painful, and generally not the highlight of the data or analytics engineers’ day,” said Knapp. “By being able to use the technology for… [pipeline automation, orchestration, and optimization] enables them to build a lot faster…[By taking] this sort of optimization piece over to an automated engine, we focus much more on the actual data pipeline itself.”
Those interested in trying out this new integration can visit Ascend’s website and contact a team member for further details.
To learn more about Ascend for dbt, please visit https://www.ascend.io/.