KDnuggets
MAY 15, 2023
Transitioning your career to DataOps could be just the change you need - not only will it provide the possibility to expand your technical skills, but also a rewarding salary with many job openings.
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.
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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.
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.
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.
Alation
APRIL 4, 2023
Building data pipelines is challenging, and complex requirements (as well as the separation of many sources) leads to a lack of trust. 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.
IBM Journey to AI blog
AUGUST 12, 2024
Consequently, AIOps is designed to harness data and insight generation capabilities to help organizations manage increasingly complex IT stacks. It uses CI/CD pipelines to automate predictive maintenance and model deployment processes, and focuses on updating and retraining models as new data becomes available.
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