Nov 15, 2018
Palo Alto, CA, USA
Apr 16, 2019   |  By Bikas Saha
Apache Spark is one of the most popular engines for distributed data processing on Big Data clusters. Spark jobs come in all shapes, sizes and cluster form factors. Ranging from 10’s to 1000’s of nodes and executors, seconds to hours or even days for job duration, megabytes to petabytes of data and simple data scans to complicated analytical workloads.
Apr 5, 2019   |  By Shioulin Sam
We are excited to release Learning with Limited Labeled Data, the latest report and prototype from Cloudera Fast Forward Labs. Being able to learn with limited labeled data relaxes the stringent labeled data requirement for supervised machine learning. Our report focuses on active learning, a technique that relies on collaboration between machines and humans to label smartly.
Apr 4, 2019   |  By Michael Wilson
Cloudera Altus Director helps you deploy, scale, and manage Cloudera clusters on AWS, Microsoft Azure, or Google Cloud Platform. Altus Director both enables and enforces the best practices of big data deployments and cloud infrastructure. Altus Director’s enterprise-grade features deliver a mechanism for establishing production-ready clusters in the cloud for big data workloads and applications in a simple, reliable, automated fashion.
Apr 2, 2019   |  By Romain Rigaux
Self-service exploratory analytics is one of the most common use cases we see by our customers running on Cloudera’s Data Warehouse solution. With the recent release of Cloudera 6.2, we continue to improve the end user query experience with Hue, focusing on easier SQL query troubleshooting and increased compatibility with Hive. Read on to learn more and try it out in one-click at
Mar 19, 2019   |  By Grant Henke
Although the Kudu server is written in C++ for performance and efficiency, developers can write client applications in C++, Java, or Python. To make it easier for Java developers to create reliable client applications, we’ve added new utilities in Kudu 1.9.0 that allow you to write tests using a Kudu cluster without needing to build Kudu yourself, without any knowledge of C++, and without any complicated coordination around starting and stopping Kudu clusters for each test.
Jun 28, 2018   |  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.
Jun 26, 2018   |  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.
Jun 12, 2018   |  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.
May 17, 2018   |  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.
May 15, 2018   |  By Cloudera
The Modern Platform for Machine Learning and Analytics Optimized for Cloud.
Apr 9, 2019   |  By Cloudera
Cloudera Fast Forward Labs’ latest machine learning research report introduces a new machine learning capability that relaxes the stringent labeled data requirement in supervised machine learning thereby opening up new product possibilities.
Mar 27, 2019   |  By Cloudera
The key challenges preventing IoT initiatives to be successful are the inability to capture and process data directly from thousands of edge devices as well as the lack of operational visibility and control of the edge. Dinesh Chandrasekhar, Director of Product Marketing for Data-in-Motion at Cloudera, talks about solutions designed to solve these IoT challenges.
Mar 27, 2019   |  By Cloudera
IoT has been transforming industries like fleet management. Cloudera enables enterprises to gain actionable intelligence in real-time with data captured from the edge using Machine Learning models refined actively over time. This video shows how Cloudera Edge Management and Cloudera Data Science Workbench work seamlessly with Cloudera Flow Management to realize the Edge2AI vision for enterprises.
Feb 13, 2019   |  By Cloudera
Sushant Rao, Director of Product Marketing for Cloud, shares how Cloudera’s data analytics and Spark platform empowers teams to develop and deploy data warehouse and machine learning in the cloud.
Jan 29, 2019   |  By Cloudera
Mike Olson talks about AI and Big Data in Government