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As insurers look to be more agile, data mesh strategies take centerstage

CIO Business Intelligence

The human political element plays a significant role here as well, as local data owners push back on relinquishing control over domain-specific data assets to centralized data governance authorities. These domain data leaders often cite the diminishing returns and significant effort of central data team engagement.

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8 data strategy mistakes to avoid

CIO Business Intelligence

At Vanguard, “data and analytics enable us to fulfill on our mission to provide investors with the best chance for investment success by enabling us to glean actionable insights to drive personalized client experiences, scale advice, optimize investment and business operations, and reduce risk,” Swann says.

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Data Preparation and Data Mapping: The Glue Between Data Management and Data Governance to Accelerate Insights and Reduce Risks

erwin

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. Creating a High-Quality Data Pipeline.

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What is Data Lineage? Top 5 Benefits of Data Lineage

erwin

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Data lineage offers proof that the data provided is reflected accurately. Data Governance.

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The Rising Need for Data Governance in Healthcare

Alation

Leaders are asking how they might use data to drive smarter decision making to support this new model and improve medical treatments that lead to better outcomes. Yet this is not without risks. This data is also a lucrative target for cyber criminals. Data governance in healthcare has emerged as a solution to these challenges.

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The importance of data ingestion and integration for enterprise AI

IBM Big Data Hub

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. This may also entail working with new data through methods like web scraping or uploading.

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Enable data analytics with Talend and Amazon Redshift Serverless

AWS Big Data

About Talend Talend is an AWS ISV Partner with the Amazon Redshift Ready Product designation and AWS Competencies in both Data and Analytics and Migration. Talend Cloud combines data integration, data integrity, and data governance in a single, unified platform that makes it easy to collect, transform, clean, govern, and share your data.