CIO

SEPTEMBER 29, 2022

And we recognized as a company that we needed to start thinking about how we leverage advancements in technology and tremendous amounts of data across our ecosystem, and tie it with machine learning technology and other things advancing the field of analytics. But we have to bring in the right talent. more than 3,000 of themâ??that

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CIO

APRIL 12, 2023

Real-time AI involves processing data for making decisions within a given time frame. Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. It isn’t easy.

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CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing.

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Cloudera

MAY 10, 2018

Click to tweet : Nominations are now open for the sixth annual Cloudera Data Impact Awards! With advancements in exploratory data science, machine learning, predictive analytics, AI, and data engineering, the world is increasingly driven by data. Grow your business. Protect your business.

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Cloudera

FEBRUARY 19, 2018

Running a large company is impossible without having an ERP system in place, and SAP business software remains at the forefront in this category. But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough.

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BPM

JANUARY 18, 2019

The current Artificial Intelligence (AI) fascination is unfortunately completely biased on Deep Neural Networks (DNN) and Machine Learning (ML) for everything. Explainable AI is a must for automated business decisions. AI-enabled data engines will provide insight about what processes can be redesigned and/or automated.

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Cloudera

DECEMBER 18, 2017

We’ve learned from these innovators that business transformation with data happens in three predictable phases, represented by the graphic below. The data-driven journey often begins with simple, tactical use cases – typically around visibility. Just as no baby runs before they crawl.

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