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

Data people face a challenge. 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. Accenture’s DataOps Leap Ahead.

DataOps 52

DataOps Data Pipeline Data Engineering Data Engineering 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

Scalable data pipelines: Seasoned data teams are facing increasing pressure to respond to a growing number of data requests from downstream consumers, which is compounded by the drive for users to have higher data literacy and skills shortage of experienced data engineers.

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Data Silos Data Pipeline DataOps Business Intelligence 102

Precisely

DECEMBER 12, 2023

For some time now, data observabilit y has been an important factor in software engineering, but its application within the realm of data stewardship is a relatively new phenomenon. Data observability is a foundational element of data operations (DataOps).

Data Observability 52

Data Observability Data Quality Data Pipeline Machine Learning 52

phData

MAY 11, 2023

Practices centered on software engineering principles can create a barrier to entry for teams with skilled data wranglers looking to take their infrastructure to the next level with cloud-native tools like Matillion for the Snowflake Data Cloud. Bitbucket, Github) to allow advanced workflows.

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ETL Analytics Analytics Data Models 52