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Next Stop – Predicting on Data with Cloudera Machine Learning

Cloudera

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

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The Ethics of AI Comes Down to Conscious Decisions

Cloudera

This blog post was written by Pedro Pereira as a guest author for Cloudera. . Right now, someone somewhere is writing the next fake news story or editing a deepfake video. Big data and AI amplify the problem. Big data algorithms are smart, but not smart enough to solve inherently human problems. Transparency is key.

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Next Stop – Building a Data Pipeline from Edge to Insight

Cloudera

You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight. The first blog introduced a mock connected vehicle manufacturing company, The Electric Car Company (ECC), to illustrate the manufacturing data path through the data lifecycle. 1 The enterprise data lifecycle.

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Top 4 Reasons Why You Should Upgrade Your Stream Processing Workloads To CDP

Cloudera

If there’s one thing enterprises have learned in 2020, it’s how to navigate through uncertain times, and in 2021, organizations will likely have to continue navigating through a shifting landscape. Today, a new modern data platform is here to transform how businesses take advantage of real-time analytics. Why upgrade to CDP now?

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The Good and the Bad of Hadoop Big Data Framework

Altexsoft

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics.

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It’s Time to Look Forward

Cloudera

As roles within organizations evolve (as seen by the growth of citizen scientists and analytics engineers) and as data needs change (think schema changes and real-time), we need more intelligent ways to perform visual exploration, data interrogation, and share insights. Change, although difficult at first, can also be very rewarding.

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Shorten time to critical insights with Streaming SQL

Cloudera

Data and analytics have become second nature to most businesses, but merely having access to the vast volumes of data from these devices will no longer suffice. Leading enterprises realize that the speed of data presents a new frontier for competitive differentiation.