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

They must put high-quality data into the hands of users as efficiently as possible. 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.

DataOps 52

DataOps Data Pipeline Data Engineering Data Engineer 52

IBM Journey to AI blog

OCTOBER 22, 2024

This adaptability allows organizations to align their data integration efforts with distinct operational needs, enabling them to maximize the value of their data across diverse applications and workflows. Organizations must support quality enhancement across structured, semistructured and unstructured data alike.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

Alation

APRIL 4, 2023

However, the race to the cloud has also created challenges for data users everywhere, including: Cloud migration is expensive, migrating sensitive data is risky, and navigating between on-prem sources is often confusing for users. To build effective data pipelines, they need context (or metadata) on every source.

DataOps 52

DataOps Data Engineering Data Engineering Data Engineer 52