Data Governance Data Integration Insurance 
CIO Business Intelligence
APRIL 29, 2022
Data-centric AI is evolving, and should include relevant data management disciplines, techniques, and skills, such as data quality, data integration, and data governance, which are foundational capabilities for scaling AI. Addressing the Challenge.
Octopai
JUNE 26, 2020
Steve, the Head of Business Intelligence at a leading insurance company, pushed back in his office chair and stood up, waving his fists at the screen. We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” Enterprise data governance. Metadata in data governance.
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erwin
FEBRUARY 7, 2019
Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down.
Cloudera
FEBRUARY 15, 2024
While there are clear reasons SVB collapsed, which can be reviewed here , my purpose in this post isn’t to rehash the past but to present some of the regulatory and compliance challenges financial (and to some degree insurance) institutions face and how data plays a role in mitigating and managing risk. Well, sort of.
Data Virtualization
MAY 26, 2022
Reading Time: 3 minutes Insurers are constantly challenged with compliance requirements changes, most of which heavily rely on excellent data management. It is crucial for insurers to examine their current data management practices with a critical eye and assess if they are setup to.
AWS Big Data
JUNE 25, 2024
It provides secure, real-time access to Redshift data without copying, keeping enterprise data in place. This eliminates replication overhead and ensures access to current information, enhancing data integration while maintaining data integrity and efficiency.
erwin
FEBRUARY 19, 2021
Automated enterprise metadata management provides greater accuracy and up to 70 percent acceleration in project delivery for data movement and/or deployment projects. It harvests metadata from various data sources and maps any data element from source to target and harmonize data integration across platforms.
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