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. data pipelines) to support.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

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.

DataOps 52

DataOps Data Engineering Data Engineer Data Engineering 52

Alation

DECEMBER 13, 2022

Cloud migration. For example, the researching buyer may seek a catalog that scores 6 for governance, 10 for self-service, 4 for cloud data migration, and 2 for DataOps (let’s call this a {6, 10, 4, 2} profile). How Does This Impact the Buyer’s Journey? Yet another user may prefer a {0, 6, 6, 8} profile.

DataOps 52

DataOps Data Governance Data Silos Data Scientist 52

Alation

AUGUST 11, 2022

DataOps sprung up to connect data sources to data consumers. The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. Data mesh says architectures should be decentralized because there are inherent problems with centralized architectures.

Data Warehouse 52

Data Warehouse Data Engineering Data Engineer Data Engineering 52