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An Overview of Cloudera’s AI Survey: The State of Enterprise AI and Modern Data Architecture

Cloudera

While every business has adopted some form of data architecture, the types they use vary widely. Navigating the complexity of modern data landscapes brings its own set of challenges. When asked about the most valuable advantages of hybrid data architectures, respondents highlighted data security (71%) as the primary benefit.

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SoftBank Selects Cloudera Data Platform to Leverage Customer Intelligence While Ensuring Data Security

Cloudera

For this reason, we have come to recognize the need for a modern data architecture that enables us to align our data strategy with our business goals. We believe these new data analysis capabilities will boost what we can offer to our customers.”

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Evaluating Change Data Capture Tools: A Comprehensive Guide

Data Engineering Weekly

CDC tools fuel analytical apps and mission-critical data feeds in banking and regulated industries, with use cases ranging from data synchronization, managing risk, and preventing fraud to driving personalization. This approach simplifies data architecture and enhances performance by reducing data movement and latency.

Data Lake 125
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How Much Data Do We Need? Balancing Machine Learning with Security Considerations

Towards Data Science

Data that isn’t interpretable generates little value if any, because you can’t effectively learn from data you don’t understand. How are you going to strategically plan for the future of your data systems? You probably need to attend to data architecture to try and keep costs from skyrocketing, but what about data retention?

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Choose Compliance, Choose Hybrid Cloud

Cloudera

Given the challenging regulatory environment, businesses processing personal data subject to the GDPR need to consider whether to store such data in a US public cloud or house it either in an EU public cloud, or behind the firewall of an EU company itself. .

Cloud 102
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Four Ways Telcos Can Realize Data-Driven Transformation

Cloudera

While navigating so many simultaneous data-dependent transformations, they must balance the need to level up their data management practices—accelerating the rate at which they ingest, manage, prepare, and analyze data—with that of governing this data.

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Data Engineering: A Formula 1-inspired Guide for Beginners

Towards Data Science

Anyways, I wasn’t paying enough attention during university classes, and today I’ll walk you through data layers using —  guess what  —  an example. Business Scenario & Data Architecture Imagine this: next year, a new team on the grid, Red Thunder Racing, will call us (yes, me and you) to set up their new data infrastructure.