Sat.Apr 13, 2024 - Fri.Apr 19, 2024

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Astera’s Guide to Insurance Data Quality and Governance

Astera

Data forms the foundation of the modern insurance industry, where every operation relies on digitized systems, including risk assessment, policy underwriting, customer service, and regulatory compliance. Adhering to robust governance frameworks allows insurers to ensure compliance with data privacy regulations.

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Harnessing Generative AI for Enhanced Customer Care Agent Coaching

Analysts Corner

Enter Generative AI (GenAI), a transformative technology that promises to revolutionize how managers coach and develop their teams. Understanding Generative AI Generative AI refers to artificial intelligence systems that can generate content, from text to simulations, by learning from vast amounts of data.

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Navigating the Future of AI in Energy: Trends, Challenges, and Opportunities

Cprime

– Generative AI (Gen AI) is transforming the energy and materials sector by enhancing efficiency, driving innovation, and supporting sustainability efforts through advanced data analysis and predictive modeling. How does Gen AI improve predictive maintenance in the energy sector?

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Data-Driven Defense: AI as the New Frontier in Business Security

Dataversity

Major business setbacks due to risk management failures happen every year. Leaders want to avoid these types of issues and rely on sound internal data management to mitigate risk and maintain confidence and […] The post Data-Driven Defense: AI as the New Frontier in Business Security appeared first on DATAVERSITY.

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How to Overcome the Pain Points of Your CRM

The promise of a CRM ( customer relationship management ) led organizations to believe each could digitally transform its businesses through tracking touchpoints throughout the buyer’s journey. However, as a company, sales stack, and database grow, it becomes difficult to uphold structure and governance to keep a CRM up-to-date.

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Exploring the Connection Between Data Governance and Data Quality

Astera

Data governance and data quality are closely related, but different concepts. The major difference lies in their respective objectives within an organization’s data management framework. Data quality is primarily concerned with the data’s condition.

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Data Professional Introspective: The Data Management Education Program

The Data Administration Newsletter

In my work with the EDM Council’s Data Management Capability Assessment Model (DCAM) 3.0 development group, we are adding a capability that has remained under the radar in our industry: the responsibility of the Data Management Program to determine concept and knowledge gaps within its staff resources.