Dataversity

SEPTEMBER 27, 2021

DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. ETL projects are increasingly based on agile processes and automated testing. Click to learn more about author Wayne Yaddow. The […].

DataOps 98

DataOps ETL Data Pipeline Data Warehouse 98

Dataversity

AUGUST 30, 2021

DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. ETL projects are increasingly based on agile processes and automated testing. Click to learn more about author Wayne Yaddow. The […].

DataOps 52

DataOps ETL Data Pipeline Data Warehouse 52

Alation

MARCH 22, 2022

DataOps has emerged as an exciting solution. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. As pressures to modernize mount, the promise of DataOps has attracted attention.

DataOps 52

DataOps Data Pipeline Data Engineering Data Engineer 52

Alation

JANUARY 25, 2022

Automated Data Orchestration (AKA DataOps). DataOps is the leading process concept in data today. See Gartner’s “ How DataOps Amplifies Data and Analytics Business Value ”). Data fabric and DataOps are a part of the continued evolution of data management-centric approaches that improve data architecture, efficiency, and quality.

DataOps 52

DataOps SQL ML ML 52

phData

MAY 11, 2023

With the “Data Productivity Cloud” launch, Matillion has achieved a balance of simplifying source control, collaboration, and dataops by elevating Git integration to a “first-class citizen” within the framework. In Matillion ETL, the Git integration enables an organization to connect to any Git offering (e.g.,

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ETL Analytics Analytics Data Modeling 52

Alation

APRIL 4, 2023

Troubleshooting data issues , for an exploding number of disjointed systems and tools, breaks self-service for data users and creates gaps in visibility for dataOps. Example of where ETL may fail for Business Users and Data Engineer and how the user can track down the source of the issue in Alation with end-to-end lineage.

DataOps 52

DataOps Data Engineering Data Engineer Data Engineering 52