Whitepaper: An Assessment of Pipeline Orchestration Approaches
Learn why task-centric workflow automation becomes unmanageable over time and why data pipeline automation is the key to speed, efficiency, and operational scale.
Webinar: Intelligent Orchestration - The Key to Declarative Data Pipelines
In this webinar, we explore how applying the declarative approach to data pipelines results in 95% less code, 10x faster build times, automated maintenance, and more efficient pipelines… oh, and much happier data engineers.
Podcast: Shining A Light on Shadow IT In Data And Analytics
In this episode, founder of Ascend.io, Sean Knapp, and Co-Founder of Zonehaven, Charlie Crocker, share their experiences of working in and with companies that have dealt with shadow IT projects and the importance of enabling and empowering the use and exploration of data and analytics.
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The current standard for pipeline orchestration relies on engineers to manually translate high-level specs into a set of tasks to be executed on a pre-defined schedule. In advancing orchestration, Ascend opted for a different approach. Taking a page from compilers and...
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Welcome to Ascend! This tutorial, the first in a three-part series on Data Lake ETL (Extract, Transform, Load) will give you a brief overview on how to quickly and easily you can accomplish the “E” of ETL to ingest data from any data source with Ascend. Ascend...
HNI Corporation is a US$2.2B workplace furnishings and hearth provider, with 19 distinct brands and global manufacturing sites. HNI is driving digital transformation of their business with data. Read below on how their decision sciences team continually improves...
SQL is one of the most well established, and powerful languages for working with data. It first emerged in the 1970s as a powerful domain-specific language (DSL) for managing data in relational database management systems (RDBMS), and has become one of the longest...
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Reposted from: As data engineers the health of our pipelines is our highest priority. Unfortunately, there are countless ways that our dataflows can break or degrade that have nothing to do with the business logic or data transformations that we write and maintain....