Data Integration Document Risk Management Strategy 
CIO Business Intelligence
NOVEMBER 21, 2023
After all, 41% of employees acquire, modify, or create technology outside of IT’s visibility , and 52% of respondents to EY’s Global Third-Party Risk Management Survey had an outage — and 38% reported a data breach — caused by third parties over the past two years.
CIO Business Intelligence
MARCH 24, 2023
The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.” Such a framework provides your organization with a holistic approach to collecting, managing, securing, and storing data.
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O'Reilly on Data
DECEMBER 12, 2019
In addition to newer innovations, the practice borrows from model risk management, traditional model diagnostics, and software testing. The study of security in ML is a growing field—and a growing problem, as we documented in a recent Future of Privacy Forum report. [8]. That’s where remediation strategies come in.
Ontotext
APRIL 6, 2023
It can apply automated reasoning to extract further knowledge and make new connections between different pieces of data. This model is used in various industries to enable seamless data integration, unification, analysis and sharing.
IBM Big Data Hub
SEPTEMBER 20, 2022
Often data scientists aren’t thrilled with the prospect of generating all the documentation necessary to meet ethical and regulatory standards. Ultimately, data management and providing users access to the right data at the right time are at the core of successful AI and AI governance.
CIO Business Intelligence
FEBRUARY 22, 2024
Increasing pressures around environment, social, and governance (ESG) concerns have organizations across industries turning to their CIOs to revamp their strategies for ESG reporting. To date, many companies have merely repurposed existing technology solutions for their ESG reporting needs. “Not
erwin
FEBRUARY 4, 2021
However, organizations still encounter a number of bottlenecks that may hold them back from fully realizing the value of their data in producing timely and relevant business insights. It uncovered a number of obstacles that organizations have to overcome to improve their data operations.
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