Cloudera

Palo Alto, CA, USA
2008
  |  By Bill Zhang
The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.
  |  By Robert Hryniewicz
We are thrilled to announce the general availability of the Cloudera AI Inference service, powered by NVIDIA NIM microservices, part of the NVIDIA AI Enterprise platform, to accelerate generative AI deployments for enterprises. This service supports a range of optimized AI models, enabling seamless and scalable AI inference.
  |  By Jacob Bengtson
The journey from a great idea for a Generative AI use case to deploying it in a production environment often resembles navigating a maze. Every turn presents new challenges—whether it’s technical hurdles, security concerns, or shifting priorities—that can stall progress or even force you to start over.
  |  By Steve Moroski
According to recent survey data from Cloudera, 88% of companies are already utilizing AI for the tasks of enhancing efficiency in IT processes, improving customer support with chatbots, and leveraging analytics for better decision-making. More and more enterprises are leveraging pre-trained models for various applications, from natural language processing to computer vision. For that reason, Cloudera is evaluating a new line of business: Cloudera Integrated Data and AI Exchange (InDaiX).
  |  By Blake Tow
Imagine a world where your sensitive data moves effortlessly between clouds – secure, private, and far from the prying eyes of the public internet. Today, we’re making that world a reality with the launch of Cloudera Private Link Network. Organizations are continuously seeking ways to enhance their data security. One of the challenges is ensuring that data remains protected as it traverses different cloud environments.
  |  By Joe Rodriguez
A prominent global bank was thrust into the spotlight for all the wrong reasons. The institution was hit with a staggering fine – multiple billions – for failing to comply with new data protection regulations that ultimately led to a customer data breach. The breach, which exposed sensitive information, not only resulted in financial penalties but also caused significant reputational damage.
  |  By Vinicius Cardoso
Without a doubt, Artificial Intelligence (AI) is revolutionizing businesses, with Australia’s AI spending expected to hit $6.4 billion by 2026. However, according to The State of Enterprise AI and Modern Data Architecture report, while 88% of enterprises adopt AI, many still lack the data infrastructure and team skilling to fully reap its benefits. In fact, over 25% of respondents stated they don’t have the data infrastructure required to effectively power AI.
  |  By Jeremiah Morrow
It’s nearing the end of the summer in North America, and one report has been a staple on my reading list for more than a decade: the Flexera State of the Cloud Report. The annual survey of hundreds of global IT decision makers assesses cloud strategies, migration trends, and important considerations for companies moving to the cloud or managing cloud environments.
  |  By Jeff Healey
The CRN Tech Innovator Awards spotlight innovative products and services across 36 categories, with winners chosen by CRN staff from over 320 product applications. This year, we’re excited to share that Cloudera’s Open Data Lakehouse 7.1.9 release was named a finalist under the category of Business Intelligence and Data Analytics.
  |  By Jeff Healey
By now, every organization, regardless of industry, has at least explored the use of AI, if not already embraced it. In today’s market, the AI imperative is firmly here, and failing to act quickly could mean getting left behind. But even as adoption soars, struggles remain, and scalability continues to be a major issue. Organizations are quick to adopt AI, but getting it established across the organization brings a unique set of challenges that come into play.
  |  By Cloudera
We have bundled the collective Cloudera support teams, implementation skill and experience into our Observability platform resulting in our framework called validations. This framework offers a clear and detailed view of potential issues within your Cloudera Environment enabling you to fix it internally. Based on years of Cloudera support experience, we identified over 400 and growing issues our customers have encountered frequently, and provide remedies. This framework also provides detailed information to provide to our support team should this issue require a more complex solution.
  |  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 cloudera.com.
  |  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
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.