Human beings tend to filter out events they deem unimportant. They can only process so much at any given time. Computer systems, however, must be able to handle a massive number of events in real time or near-real time to help support a wide range of applications. Financial applications must monitor events to help counter … Continue reading New hyper-fast data ingestion enables smarter decisions
Tag: Data Science
Information analytics has never been a “one size fits all” proposition. That applies to the hardware and software technologies organizations employ, the information being parsed and the goals of specific projects. So it’s worth examining how individual vendors approach analytics and the way they evolve their solutions and services to reflect changes in commercial markets. … Continue reading IBM launches new Integrated Analytics System with Machine Learning
Everywhere you go today, people are looking down at a mobile device. They are online, browsing, collaborating, shopping for goods and services and transacting business. And not just consumers are using them. Mobile devices are also being used extensively in business-to-business transactions. Customers and prospects have become empowered in the online world. Social networks and … Continue reading Why big data?
Cloudera Data Science Workbench (CDSW) provides data science teams with a self-service platform for quickly developing machine learning workloads in their preferred language, with secure access to enterprise data and simple provisioning of compute. Individuals can request schedulable resources (e.g. compute, memory, GPUs) on a shared cluster that is managed centrally. While self-service provisioning of … Continue reading New in Cloudera Data Science Workbench 1.2: Usage Monitoring for Administrators
how to use Deeplearning4J (DL4J) along with Apache Hadoop and Apache Spark to get state-of-the-art results on an image recognition task. Continuing on a similar stream of work, in this post we discuss a viable alternative that is specifically designed to be used with Spark, and data available in Spark and Hadoop clusters via a … Continue reading Deep Learning with Intel’s BigDL and Apache Spark
Since the birth of big data, Cloudera University has been teaching developers, administrators, analysts, and data scientists how to use big data technologies. We have taught over 50,000 folks all of the details of using technologies from Apache such as HDFS, MapReduce, Hive, Impala, Sqoop, Flume, Kafka, Core Spark, Spark SQL, Spark Streaming, and Spark … Continue reading Big Data Architecture Workshop
Hadoop is a Java-based, open source framework that supports companies in the storage and processing of massive data sets. Currently, many firms still struggle with interpreting Hadoop’s software and are doubtful about whether or not they can depend on it for delivering projects. Even so, it's essential to understand just how much Hadoop enables businesses … Continue reading How to Best Leverage the Services of Hadoop Big Data?