Palo Alto, CA, USA
  |  By David Dichmann
Artificial intelligence (AI) is something that, by its very nature, can be surrounded by a sea of skepticism but also excitement and optimism when it comes to harnessing its power. With the arrival of the latest AI-powered technologies like large language models (LLMs) and generative AI (GenAI), there’s a vast amount of opportunities for innovation, growth, and improved business outcomes right around the corner. All of that technology, though, depends on data to be successful.
  |  By Joe Rodriguez
Regulations often get a bad rap. You may have heard the old idiom “cut the red tape” which means to circumvent obstacles like regulations or bureaucracy. But in many – if not most )– cases the underlying need for regulations outweighs the burden of compliance.
  |  By Natalia Belaya
It’s been said that the Federal Government is one of, if not the largest, producer of data in the United States, and this data is at the heart of mission delivery for agencies across the civilian to DoD spectrum. Data is critical to driving the innovation and decision-making that improves services, streamlines operations and strengthens national security.
  |  By Navita Sood
We’re excited to share that Gartner has recognized Cloudera as a Visionary among all vendors evaluated in the 2023 Gartner® Magic Quadrant™ for Cloud Database Management Systems. This recognition underscores Cloudera’s commitment to continuous customer innovation and validates our ability to foresee future data and AI trends, and our strategy in shaping the future of data management.
  |  By Abhas Ricky
At a time when AI is exploding in popularity and finding its way into nearly every facet of business operations, data has arguably never been more valuable. More recently, that value has been made clear by the emergence of AI-powered technologies like generative AI (GenAI) and the use of Large Language Models (LLMs).
  |  By Abhas Ricky
The ongoing progress in Artificial Intelligence is constantly expanding the realms of possibility, revolutionizing industries and societies on a global scale. The release of LLMs surged by 136% in 2023 compared to 2022, and this upward trend is projected to continue in 2024. Today, 44% of organizations are experimenting with generative AI, with 10% having already implemented it in operational settings. Companies must act now in order to stay in the AI Race.
  |  By Blake Tow
As enterprise AI technologies rapidly reshape our digital environment, the foundation of your cloud infrastructure is more critical than ever. That’s why Cloudera and Red Hat, renowned for their open-source solutions, have teamed up to bring Red Hat Enterprise Linux (RHEL) to Cloudera on public cloud as the operating system for all of our public cloud platform images. Let’s dive into what this means and why it’s a game-changer for our customers.
  |  By Wim Stoop
Artificial Intelligence (AI) is primed to reshape the way just about every business operates. Cloudera research projected that more than one third (36%) of organizations in the U.S. are in the early stages of exploring the potential for AI implementation. But even with its rise, AI is still a struggle for some enterprises. AI, and any analytics for that matter, are only as good as the data upon which they are based. And that’s where the rub is.
  |  By Pablo Quinones
In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. This will allow a data office to implement access policies over metadata management assets like tags or classifications, business glossaries, and data catalog entities, laying the foundation for comprehensive data access control.
  |  By Tamas Barnabas Egyed
Businesses often need to aggregate topics because it is essential for organizing, simplifying, and optimizing the processing of streaming data. It enables efficient analysis, facilitates modular development, and enhances the overall effectiveness of streaming applications. For example, if there are separate clusters, and there are topics with the same purpose in the different clusters, then it is useful to aggregate the content into one topic.
  |  By Cloudera
Managing and forecasting cluster resource consumption costs is a complex task. Inefficient resource allocations and usage can lead to budget overruns and unexpected expenses. The challenge lies in gaining comprehensive insights into your resource consumption across different regions, departments, and user groups. It's also crucial for accurate financial planning. Cloudera Observability provides powerful financial governance capabilities to tackle these challenges effectively by providing unparalleled insight and control over your resource consumption and costs.
  |  By Cloudera
Firas Yasin, Global Alliance Manager of AI/ML at RedHat, introduces the RedHat and Cloudera partnership. Firas shares that customers are often missing the combination of security, scalability and support when deploying open-source solutions for their end-to-end data lifecycles. In this video, Firas highlights that together with RedHat OpenShift and Cloudera Data Platform, customers can achieve security and scalability through the joint solution, in addition to catalyzing on RedHat and Cloudera’s unrivaled support offerings.
  |  By Cloudera
Cloudera Observability provides the ability to define system rules and automate the appropriate action when those rules are broken through Auto Actions. This prevents for example that any one , query or job monopolizes the system, thereby impacting overall system performance.
  |  By Cloudera
Introduction to Apache Airflow: A brief overview for both beginners and enthusiasts. Best Practices and Use Cases: Learn from industry experts about optimizing your workflows and real-world use cases.
  |  By Cloudera
Unlock data potential with Cloudera's Open Data Lakehouse powered by Apache Iceberg. Break silos, centralize security, and accelerate AI, BI, and machine learning projects. Collaboration made efficient. Learn more at
  |  By Cloudera
Ozone enables ingest, processing, exploration, efficient iterative training, and fine-tuning of LLMs that rely on huge structured and unstructured datasets. This demo illustrates that. We have deployed a CML AMP chatbot that uses an LLM, augmented with an existing knowledge base. The knowledge base is stored in Ozone and retrieved over S3.
  |  By Cloudera
No matter where you are in your data journey, Cloudera and AWS can help maximize your insights – providing flexibility, scale, and governance.
  |  By Cloudera
Join Ehrar Jameel, Head of Data and Analytics, as he demystifies the concept of data strategy in this enlightening snippet from our Art of Data Leadership series. In this segment, Ehrar delves into the fundamental question: What is a data strategy? Ready to delve deeper into the world of data leadership? Click here for the full Art of Data Leadership playlist and gain invaluable insights from Ehrar and other industry experts.
  |  By Cloudera
As organizations look to decrease cloud costs and run more efficiently, Cloudera DataFlow 2.6 introduced several improvements like Zookeeper-less deployments, new storage profiles, improved suspend behavior and vertical scaling.
  |  By Cloudera
Explore how Geodis, a global logistics powerhouse, stays ahead of the curve in an ever-changing industry. Witness how they leverage real-time data and innovative solutions from Cloudera to streamline operations, enhance visibility, and exceed customer expectations, propelling their business forward in a world that never stops moving.
  |  By Cloudera
Enterprises require fast, cost-efficient solutions to the familiar challenges of engaging customers, reducing risk, and improving operational excellence to stay competitive. The cloud is playing a key role in accelerating time to benefit from new insights. Managed cloud services that automate provisioning, operation, and patching will be critical for enterprises to leverage the full promise of the cloud when it comes to time to value and agility.
  |  By Cloudera
The adoption of cloud computing in the financial services sector has grown substantially in the past three years on a global basis. Diversification of risk is always a key concern for financial institutions and the seeming safety of having a single cloud provider is not being properly measured from a systemic risk and operational risk perspective.
  |  By Cloudera
This white paper provides a reference architecture for running Enterprise Data Hub on Oracle Cloud Infrastructure. Topics include installation automation, automated configuration and tuning, and best practices for deployment and topology to support security and high availability.
  |  By Cloudera
A cloud-based analytics platform needs to be easy, unified, and enterprise-grade to meet the demands of your business. This white paper covers how Cloudera's machine learning and analytics platform complements popular cloud services like Amazon Web Services (AWS) and Microsoft Azure, and enables customers to organize, process, analyze, and store data at large scale...anywhere.
  |  By Cloudera
The Modern Platform for Machine Learning and Analytics Optimized for Cloud.
  |  By Cloudera
In the wake of the global financial crisis, the world has become much more interconnected and immensely more complex. As a result, you can no longer simply look at the past as an indicator of future trends. The financial services industry needs real-time insights into numerous interacting variables to make informed decisions.

Cloudera delivers the modern platform for machine learning and analytics optimized for the cloud. Imagine having access to all your data in one platform. The opportunities are endless. We enable you to transform vast amounts of complex data into clear and actionable insights to enhance your business and exceed your expectations.

The right products for the job:

  • Enterprise Data Hub: Operate with confidence—thanks to comprehensive security and governance—while at the same time enabling unrivaled self-service performance at extreme scale. All in an enterprise-grade solution that lets you run anywhere, on-premises or in hybrid- and multi-cloud environments.
  • Data Science Workbench: Accelerate machine learning from research to production with the secure, self-service enterprise data science platform built for the enterprise.
  • Data Warehouse: A modern data warehouse that delivers an enterprise-grade, hybrid cloud solution designed for self-service analytics.
  • Data Science & Engineering: Cloudera Data Science provides better access to Apache Hadoop data with familiar and performant tools that address all aspects of modern predictive analytics.
  • Altus Cloud: The industry’s first machine learning and analytics cloud platform built with a shared data experience.

The world’s leading organizations choose Cloudera to grow their businesses, improve lives, and advance human achievement.