Palo Alto, CA, USA
Jun 17, 2019 | By Jeff Fletcher
Once the data science is done (and you know where your data comes from, what it looks like, and what it can predict) comes the next big step: you now have to put your model into production and make it useful for the rest of the business. This is the start of the model operations life cycle. The key focus areas (detailed in the diagram below) are usually managed by machine learning engineers after the data scientists have done their work.
Jun 10, 2019 | By Xiao Chen
HDFS erasure coding (EC), a major feature delivered in Apache Hadoop 3.0, is also available in CDH 6.1 for use in certain applications like Spark, Hive, and MapReduce. The development of EC has been a long collaborative effort across the wider Hadoop community. Including EC with CDH 6.1 helps customers adopt this new feature by adding Cloudera’s first-class enterprise support.
Jun 6, 2019 | By Michael Gregory
Imagine that you are a Chief Data Officer at a major telecommunications provider and the CEO has asked you to overhaul the existing customer churn analytics. The current process relies on manual export of data from dozens of data sources including ERP, CRM, and Call Detail Record (CDR) databases onto a user’s PC.
Jun 3, 2019 | By Tristan Stevens
Cloudera Search is a highly scalable and flexible search solution based on Apache Solr which enables exploration, discovery and analytics over massive, unstructured and semi-structured datasets (for example logs, emails, dna-strings, claims forms, jpegs, xls sheets, etc). It has been adopted by a large number of Cloudera customers across a wide range of industries for high ROI and SLA-bound workloads, with many of those having strict requirements around security and compliance.
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 22, 2019 | By Cloudera
Using Cloudera technology as the platform, a connected car can gather a significant amount of data, ranging from other vehicles, road infrastructure and even pedestrians. The connected car ecosystem enriches the driving experience and especially makes for a safer driving environment.
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.