Data Engineering

Data Transformation Explained

Data transformation is the process of converting data from one format or structure to another. Ascend makes data transformation more efficient and automated. … Read More

How Automation Delivers More Business Value | Partner Webinar Series

In this installment of the Ascend partner webinar series we talk with Cyrus Facciano and Jared Langguth, the principals of X is Y, about their secret sauce to helping major enterprises create business value with technology and automation.  … Read More

Three Mistakes Data Engineering Managers Make That Slow Down Development (And How to Speed It Back Up)

Leading data teams is challenging. Few technological domains have undergone such rapid change over the past few years. Yet the vast majority of data teams, 96% to be exact, are at or over capacity. … Read More

D-SHAs: Smarter, Faster, and More Efficient Pipelines with Incremental Data Shas

We are excited to announce D-SHAs, a mechanism used to actively check intermediate data and halt downstream processing that is simply not necessary. … Read More

Negotiating the Release From Accidental Ransomware

In this episode, we discuss the concept of accidental ransomware—or when a team is slowed down by the burden of managing and maintaining commoditized software. … Read More

Autopiloting Snowflake ETL with the Data Automation Cloud

In this episode, we do things a bit differently and chat with one of Ascend’s lead engineers, Nandan Tammineedi, about his work helping develop the Ascend for Snowflake platform. … Read More

Data Automation: The Pros and Pros. Are there Cons?

In this episode, we look at a foundational aspect of data engineering workloads—automation, including the confusion that frequently surrounds data automation and how some data teams can avoid the major pitfall of going too far too fast. … Read More

Orchestrating Data for Success with Automation

In this episode, we chat about one of the foundational principles of data engineering—data orchestration. What is it, who needs it, and just how data engineering organizations need it to evolve over the next few years. … Read More

Common Change Data Capture Usage Patterns

Change Data Capture (CDC) is a common technique to track data changed in a database system. Then downstream systems, instead of fully resyncing, can operate on the incremental changes. … Read More

Practices for Data Warehousing with Ascend—Automate the Data Warehouse as a Projection

In this second post in the series “Practices for Data Warehousing with Ascend”, we’ll explore the concept of automating the management of a data warehouse through the projection of source data. … Read More