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Manage your data warehouse cost allocations with Amazon Redshift Serverless tagging

AWS Big Data

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. Michael Yitayew is a Product Manager for Amazon Redshift based out of New York. He has supported AWS customers for over 3 years in both product marketing and product management roles.

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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. This will be your OLTP data store for transactional data. version cluster.

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Liberty Mutual CIO Monica Caldas on developing a digital-savvy workforce

CIO Business Intelligence

If we understand the data better and derive better insights, it enables us to offer better products and services at greater speed. We have modernized most of our data warehouses, we have put in new tools and capabilities, and that’s great, because now we’re at this next inflection point of technology with gen AI.

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Your Effective Roadmap To Implement A Successful Business Intelligence Strategy

datapine

Improved risk management: Another great benefit from implementing a strategy for BI is risk management. This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization?

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Integrating Data Governance and Enterprise Architecture

erwin

To better understand and align data governance and enterprise architecture, let’s look at data at rest and data in motion and why they both have to be documented. Documenting data at rest involves looking at where data is stored, such as in databases, data lakes , data warehouses and flat files.

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Data Governance Makes Data Security Less Scary

erwin

While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed.

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Bringing Financial Services Business Use Cases to Life: Leveraging Data Analytics, ML/AI, and Gen AI

Cloudera

In this context, Cloudera and TAI Solutions have partnered to help financial services customers accelerate their data-driven transformation, improve customer centricity, ensure compliance with regulations, enhance risk management, and drive innovation.