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

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. People want to know how to implement DataOps successfully.

DataOps 52

DataOps Data Pipeline Data Engineering Data Engineering 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

Alation

JUNE 21, 2022

The audience grew to include data scientists (who were even more scarce and expensive) and their supporting resources (e.g., ML and DataOps teams). After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that. data pipelines) to support.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

IBM Journey to AI blog

OCTOBER 22, 2024

The ability to effectively deploy AI into production rests upon the strength of an organization’s data strategy because AI is only as strong as the data that underpins it. Organizations must support quality enhancement across structured, semistructured and unstructured data alike.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102

Precisely

SEPTEMBER 18, 2023

Regardless of your industry or role in the business, data has a massive role to play – from operations managers who rely on downstream analytics for important business decisions, to executives who want an overview of how the company is performing for key stakeholders. Trusted data is crucial, and data observability makes it possible.

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Data Observability Data Quality Data Pipeline DataOps 52