Dataconomy

DECEMBER 22, 2022

DataOps presents a holistic approach to designing, building, moving, and utilizing data within an organization. It aims to maximize the business value of data and its underlying infrastructure, both on-premises and in the cloud. However, DataOps should […].

DataOps 91

DataOps Data Governance Database Data Science 91

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 Engineer 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.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

Dataversity

OCTOBER 22, 2021

In today’s competitive enterprise landscape, having a proper DataOps strategy in place correlates with better data intelligence and optimization within an organization – breaking down silos and enabling data democratization and better business agility at scale.

DataOps 98

DataOps Data Governance Database 98

Precisely

FEBRUARY 9, 2024

Reporting standards are also becoming increasingly stringent, and data integrity capabilities help ensure that metrics are clear, accurate, and readily accessible. Going into 2024, we see a continued trend towards enabling democratized delivery of data across business functions with repeatable, scalable processes.

Data Quality 69

Data Quality DataOps Data Silos Artificial Intelligence 69