Precisely

JULY 15, 2024

Quality and formatting may differ with more autonomous domain teams producing data assets, making interoperability difficult and data quality guarantees elusive. Data discoverability and reusability. Data products must be properly designed and organized to be reused across the organization.

Data Governance 72

Data Governance DataOps Data Silos Data Pipeline 72

Alation

MAY 31, 2023

And don’t miss my demo presentation at the booth! We’ll have a team on-site and encourage you to stop by our booth in the exhibit hall.

Data Governance 52

Data Governance DataOps Data Pipeline Business Intelligence 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. So we have to be very careful about giving the domains the right and authority to fix data quality. Tools became stacks.

Data Warehouse 52

Data Warehouse Data Engineering Data Engineering Data Engineering 52

Alation

OCTOBER 12, 2021

Enterprise data analytics integrates data, business, and analytics disciplines, including: Data management. Data engineering. DataOps. … In the past, businesses would collect data, run analytics, and extract insights, which would inform strategy and decision-making. Evaluate and monitor data quality.

Analytics 52

Analytics Analytics Data Governance DataOps 52

phData

MAY 7, 2025

It provides a broader view of data organization compared to the all_data_files table. A Paradigm Shift for DataOps and Platform Teams These metadata tables represent more than just internal logsthey serve as powerful, queryable assets that DataOps and platform engineering teams can actively automate against. format(",".join([f"'{oid}'"

DataOps 52

DataOps AWS SQL Data Engineering 52