Tag: Hadoop

Are you struggling with the cost of adding more and more datasources? Of doing complex transformations across growing volumes of data? Of rapidly incorporating complex data objects into your data warehouse? Big data technologies are not just for internet companies or your new social-media application. Attend this session to learn how Oracle Big Data Appliance,…

A case study to provide valuable information and quick wins in selecting visualization tools for Big Data in your Enterprise. As organizations embrace Big Data for Business Insights, it is very clear that business decision makers need to derive more valuable information from Big Data. Big Data created extraordinary capabilities for business to achieve faster…

This session will walk through several practical example of using Hadoop in the companies who've been traditional users of relational Oracle databases. We will look into such ares as ETL, archival storage as well as analytics.

Frequently the terms NoSQL and Big Data are conflated – many view them as synonyms. It’s understandable – both technologies eschew the relational data model and spread data across clusters of servers, versus relational database technology which favors centralized computing. But the “problems” these technologies address are quite different. Hadoop, the Big Data poster child,…

The volumes of digital data have been growing exponentially since the dawn of the computer revolution. By 2003 we had accumulated only 1 billion gigabytes (1 petabyte) of data, while in 2011 alone 1 trillion gigabytes was created – and much of this data does not always fit nicely into pre-existing schemas. The Big Data…

From tracking customers in online stores to tweets and blog posts, unstructured data is rapidly growing and businesses are looking for ways to analyze it. In this presentation, I will explain why storing and processing unstructured data is a challenge best answered by specialized systems such as Hadoop, I will dive into how Hadoop works…

Hadoop has become a popular platform for managing large datasets of structured and unstructured data. It does not replace existing infrastructure, but instead augments them. Most companies will still use relational databases for transaction processing and low-latency queries, but can benefit from Hadoop for reporting, machine learning or ETL.

Originally Broadcasted: January 9th, 2013 Featured Speaker: Gwen Shapira, Senior Consultant From tracking customers in online stores to tweets and blog posts, unstructured data is rapidly growing and businesses are looking for ways to analyze it. In this presentation, I will explain why storing and processing unstructured data is a challenge best answered by specialized…

Machine learning is one of the valuable applications using Big Data. And it is coming to Hadoop through a new Apache project called Mahout. Apache Mahout is a project that provides a set of machine learning algorithms that can be executed on top of Hadoop to analyze big data sets. In this presentation, the speaker…

With the great interest in ‘Big Data’ solutions, hear why the Oracle platform is perfect for ‘Big Data’ requirements with analytic and SQL capabilities to join ALL data types, including relational, Spatial, XML, text, semantics, multimedia and other unstructured data. Get an introduction into the features in Oracle Database for storing, managing and analyzing unstructured…