Big data and Hadoop tools will increasingly allow companies to utilize customer insights to improve their services and increase productivity.
Big Data Insights
Last week I had the pleasure of attending a workshop at Imperial College London on The Future of Big Data Management. This was organized by some of the CERN physicists who were interested in bringing together scientists across different fields together with those of us in the computing industry working on some of the same problems.
CERN’s Hadron Collider Experiments -ATLAS and CMS being the big two- are the latest in a long line of particle detectors that have always stressed the computing, network and storage technologies of the time. …
As analytics platforms like Hadoop become more powerful and user-friendly, the market for intelligent business software will continue to grow.
At the Hadoop Summit, industry analysts touted YARN as an evolutionary step in processing Hadoop HDFS and improving enterprise big data operations.
Implementing sophisticated, real-time analysis for big data insights can be an easy process with Apache Hadoop and MapReduce.
Apache Hadoop has quickly risen from a promising curiosity to a industry leader, based on its high performance and many applications.
The myriad benefits of Hadoop clusters have positioned Apache Hadoop as the leading platform for big data analytics.
Breaking down the Hadoop ecosystem into its stages sheds light on how the whole environment works.
A technology-centric university recently announced the construction of a state-of-the-art research facility for its big data projects.
Circumventing big data hurdles with Apache Hadoop and Hortonworks
Big data analytics have gained in popularity over the last few years, yet many operations continue to struggle with their implementation. Not all analytics platforms are created equal and businesses may find that a hastily chosen application is unsuitable for their needs and existing capabilities. For instance, only the most high-quality solutions will facilitate the use of unstructured data. The scope of a data analytics project can be greatly improved by incorporating difficult-to-quantify information sources such as audio and video recordings, allowing researchers to dig deeper into the data pool and glean more actionable insights.…
Although launching a big data project presents certain challenges, Hortonworks and Apache Hadoop can help organizations eliminate those issues.
The question of whether data can be effectively processed in Hadoop is dependent on the user strategy, not the information itself.
Hortonworks’ recent partnership with Red Hat is poised to provide Apache Hadoop users with greater flexibility integrating storage solutions and enterprise file systems.
Apache Hadoop can benefit the healthcare sector, which needs user-friendly ways to effectively store and apply data for improving medical care.
Hadoop HBase is an essential component of Apache Hadoop, simplifying big data storage and making its retrieval and usage more efficient.