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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. Regulation and risk are a big focus for financial institutions.

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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. version cluster.

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How IBM and AWS are partnering to deliver the promise of AI for business

IBM Big Data Hub

A leading insurance player in Japan leverages this technology to infuse AI into their operations. Real-time analytics on customer data — made possible by DB2’s high-speed processing on AWS — allows the company to offer personalized insurance packages.

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Top 10 Reasons for Alation with Snowflake: Reduce Risk with Active Data Governance

Alation

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Two problems arise.

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Accenture’s Smart Data Transition Toolkit Now Available for Cloudera Data Platform

Cloudera

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

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A New Era in Data Warehousing

Cloudera

It goes unnoticed but cyber threats are routinely hunted down by correlating hundreds of attributes from disparate data sources – even as data types and formats evolve. Leading insurers are underwriting policies with lower risks. We call it ‘Modern Data Warehousing’. Hybrid compute. Hybrid storage.

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Data Modeling 101: OLTP data modeling, design, and normalization for the cloud

erwin

I was pricing a data warehousing project with just 4 TB of data – small by today’s standards. I chose “OnDemand” for up to 64 virtual CPUs and 448 GB of memory, since this data warehouse wanted to leverage in-memory processing. So that’s $136,000 per year just to run this one data warehouse in the cloud.