Systems | Development | Analytics | API | Testing

5 Success Stories That Show the Value of Enterprise Data Cloud

What’s the fastest and easiest path towards powerful cloud-native analytics that are secure and cost-efficient? In our humble opinion, we believe that’s Cloudera Data Platform (CDP). And sure, we’re a little biased—but only because we’ve seen firsthand how CDP helps our customers realize the full benefits of public cloud.

10 Steps to Achieve Enterprise Machine Learning Success

You’ve probably heard it more than once: Machine learning (ML) can take your digital transformation to another level. It’s a pie-in-the-sky statement that sounds great, right? And while you’d be forgiven for thinking that it might sound too good to be true, operational ML is, in fact, achievable and sustainable. You can get the very kind of ML you need to increase revenue and lower costs. To help teams work smarter and do things faster.

The Key to Unlocking IT Modernization's Power? Enterprise level Transformation

The United States Veterans Administration (VA) over the last decade underwent a massive enterprise-wide IT transformation, eliminating its fragmented shadow IT and adopting a centralized system capable of supporting the agency’s 400,000 employees and more effectively utilizing its $240 billion-plus annual budget. The result: A more reliable and modern IT environment that improves access, availability, and user experience -ultimately supporting the VA mission more effectively.

Enabling NVIDIA GPUs to accelerate model development in Cloudera Machine Learning

When working on complex, or rigorous enterprise machine learning projects, Data Scientists and Machine Learning Engineers experience various degrees of processing lag training models at scale. While model training on small data can typically take minutes, doing the same on large volumes of data can take hours or even weeks. To overcome this, practitioners often turn to NVIDIA GPUs to accelerate machine learning and deep learning workloads.

Next Stop - Predicting on Data with Cloudera Machine Learning

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. The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization.

Cloudera Honored With 5-Star Rating in the 2021 CRN Partner Program Guide

Cloudera is being acknowledged by CRN®, a brand of The Channel Company, in its 2021 Partner Program Guide. This annual guide provides a conclusive list of the most distinguished partner programs from leading technology companies that provide products and services through the IT Channel. The 5-Star rating is awarded to an exclusive group of companies that offer solution providers the best of the best, going above and beyond in their partner programs.

Hybrid Cloud and Strategic Data Use Accelerate State, Army Missions

Some of the most forward-operational elements of the United States federal government are making strides in leveraging data through hybrid cloud environments—and they’re constantly evaluating progress and recalibrating their approaches along the way. At agencies including the Army and the State Department, work is well underway to find ways of employing emerging technologies that build on cloud services and data optimization to realize new levels of effectiveness.

Cloudera Data Platform extends Hybrid Cloud vision support by supporting Google Cloud

CDP Public Cloud is now available on Google Cloud. The addition of support for Google Cloud enables Cloudera to deliver on its promise to offer its enterprise data platform at a global scale. CDP Public Cloud is already available on Amazon Web Services and Microsoft Azure. With the addition of Google Cloud, we deliver on our vision of providing a hybrid and multi-cloud architecture to support our customer’s analytics needs regardless of deployment platform.