Dataversity

DECEMBER 14, 2020

It was only a few years ago that BI and data experts excitedly claimed that petabytes of unstructured data could be brought under control with data pipelines and orderly, efficient data warehouses. But as big data continued to grow and the amount of stored information increased every […].

DataOps 59

DataOps Data Pipeline Data Warehouse Big Data 59

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. The post DataOps Highlights the Need for Automated ETL Testing (Part 2) appeared first on DATAVERSITY. Click to learn more about author Wayne Yaddow. The […].

DataOps 98

DataOps ETL Data Pipeline Data Warehouse 98

Alation

SEPTEMBER 28, 2022

What exactly is DataOps ? The term has been used a lot more of late, especially in the data analytics industry, as we’ve seen it expand over the past few years to keep pace with new regulations, like the GDPR and CCPA. In essence, DataOps is a practice that helps organizations manage and govern data more effectively.

DataOps 52

DataOps Data Pipeline Data Quality Analytics 52

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. The post DataOps Highlights the Need for Automated ETL Testing (Part 1) appeared first on DATAVERSITY. Click to learn more about author Wayne Yaddow. The […].

DataOps 52

DataOps ETL Data Pipeline Data Warehouse 52

Precisely

SEPTEMBER 18, 2023

Author’s note: this article about data observability and its role in building trusted data has been adapted from an article originally published in Enterprise Management 360. Is your data ready to use? Trusted data is crucial, and data observability makes it possible.

Data Observability 52

Data Observability Data Quality Data Pipeline DataOps 52

Dataversity

JULY 1, 2022

A 20-year-old article from MIT Technology Review tells us that good software “is usable, reliable, defect-free, cost-effective, and maintainable. Businesses rely on data to drive revenue and create better customer experiences – […]. And software now is none of those things.” Today, most businesses would beg to differ.

Analytics 52

Analytics Analytics DataOps Data Pipeline 52