IBM Data Science in Practice

NOVEMBER 28, 2022

Insights from data gathered across business units improve business outcomes, but having heterogeneous data from disparate applications and storages makes it difficult for organizations to paint a big picture. How can organizations get a holistic view of data when it’s distributed across data silos?

Data Pipeline 130

Data Pipeline Data Quality Data Preparation Data Governance 130

Precisely

FEBRUARY 2, 2023

This requires access to data from across business systems when they need it. Data silos and slow batch delivery of data will not do. Stale data and inconsistencies can distort the perception of what is really happening in the business leading to uncertainty and delay.

Data Pipeline 52

Data Pipeline Data Silos Database Data Observability 52

Precisely

FEBRUARY 9, 2024

They’re where the world’s transactional data originates – and because that essential data can’t remain siloed, organizations are undertaking modernization initiatives to provide access to mainframe data in the cloud. That approach assumes that good data quality will be self-sustaining.

Data Quality 69

Data Quality DataOps Data Silos Artificial Intelligence 69

Precisely

OCTOBER 12, 2023

This includes understanding the impact of change within one data element on the various other data elements and compliance requirements throughout the organization. Creating data observability routines to inform key users of any changes or exceptions that crop up within the data, enabling a more proactive approach to compliance.

Data Quality 64

Data Quality Data Governance ML ML 64