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Improve Underwriting Using Data and Analytics

Cloudera

To me, this means that by applying more data, analytics, and machine learning to reduce manual efforts helps you work smarter. Simply stated, this approach enables data to be collected from any location and reside in any location for analytics to then be performed. Step two: expand machine learning and AI.

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Your Parents Still Don’t Know What a Hashtag Is. Let’s Teach Them the Basics of Machine Learning and Streaming Data

Cloudera

Imagine if you had to explain what machine learning is and how to use it. Cloudera produced a series of ebooks — Production Machine Learning For Dummies , Apache NiFi For Dummies , and Apache Flink For Dummies (coming soon) — to help simplify even the most complex tech topics. There’s no need to panic.

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Does Financial Crime Increase During a Recession?

Cloudera

They are continuously refining and tuning, using a combination of machine learning models, predictive analytics, and neural networks to predict suspicious behaviors. Our latest ebook highlights some of the advancements accomplished by UOB, Regions Bank, BRI, and Santander. . We must keep improving.

eBook 83
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Winning With Data in the Fight Against Fraud, Waste, and Abuse

Cloudera

A team approach: rich, scalable data analytics from Cloudera, GAI, Dell, and NVIDIA. These platforms become even more powerful when integrated with AI and machine learning, as well as other forms of automation. FWA is as much a data problem as it is a financial one. This leaves an open question, however: How best to get there?

Data 96
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Accessing Kafka’s Real-Time Analytics Is Easier Than Ever

TIBCO - Connected Intelligence

More and more major companies are realizing the full value of having real-time data-driven analytics at their fingertips. However, many businesses still have not been able to take advantage of the benefits of the “real-time” aspect of these analytics. . Reading Time: 2 minutes. The Problem with Kafka: Accessing Real-Time Information.

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Not Getting the Most From Your Model Ops? Why Businesses Struggle With Data Science and Machine Learning

TIBCO - Connected Intelligence

Companies have begun to recognize the value of integrating data science (DS) and machine learning (ML) across their organization to reap the benefits of the advanced analytics they can provide. What are the barriers keeping businesses from operationalizing data science and machine learning? Reading Time: 2 minutes.

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The Future Of The Telco Industry And Impact Of 5G & IoT – Part II

Cloudera

That requires real-time analytics and companies will have to have the capability to ingest and handle real-time streaming data. . That is where the value of streaming analytics, edge, and cloud is, in how businesses use this real-time data to inform decisions. . However, the edge cannot function in a vacuum.

IoT 109