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Are enterprises ready to adopt AI at scale?

CIO Business Intelligence

The path to achieving AI at scale is paved with myriad challenges: data quality and availability, deployment, and integration with existing systems among them. Another challenge here stems from the existing architecture within these organizations. Building a strong, modern, foundation But what goes into a modern data architecture?

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How to Manage Risk with Modern Data Architectures

Cloudera

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

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How A Data Catalog Enhances Data Risk Management

Alation

Alation joined with Ortecha , a data management consultancy, to publish a white paper providing insights and guidance to stakeholders and decision-makers charged with implementing or modernising data risk management functions. The Increasing Focus On Data Risk Management.

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Driving Success With a Modern Data Architecture and a Hybrid Approach in the Financial Services and Telco Industries

Cloudera

It supports business objectives like increasing revenues, improving customer experience, and driving profitability by giving business units and users access to relevant data so they can quickly gain the insight they need. This does not mean ‘one of each’ – a public cloud data strategy and an on-prem data strategy.

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Back to the Financial Regulatory Future

Cloudera

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.

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Using Strategic Data Governance to Manage GDPR/CCPA Complexity

erwin

Modern, strategic data governance , which involves both IT and the business, enables organizations to plan and document how they will discover and understand their data within context, track its physical existence and lineage, and maximize its security, quality and value. Strengthen data security. How erwin Can Help.

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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

Amazon Redshift features like streaming ingestion, Amazon Aurora zero-ETL integration , and data sharing with AWS Data Exchange enable near-real-time processing for trade reporting, risk management, and trade optimization. Ruben Falk is a Capital Markets Specialist focused on AI and data & analytics.