An straightforward overview of 16 core Hadoop ecosystem concepts. No Big Picture discussion, just the facts.
Apache Spark had robust machine learning, graph, streaming, and in-memory capability to the Hadoop-centric ecosystem. In 2016, we expect adoption in diverse big data, advanced analytics, data science, Internet of Things, and other application domains.
Execute and manage a team to support structure, processing, and analyzing of high volume, high velocity, or other resource intensive data to generate insight to influence marketing business decisions.
Structure, process, and analyze high volume, high velocity, or other resource intensive data to support insight to influence marketing business decisions.
We discuss categorization of e-commerce analytics, opportunities/ challenges of Big Data, Astro predictive model for Hadoop cluster management, and Apache Kylin.
Why MapR declined to participate in the Open Data Platform? Our concerns include redundancy with Apache Software Foundation Governance, misdefined “core”, and lack of participation from Hadoop leaders.
Hadoop tools develop at a rapid rate, and keeping up with the latest can be difficult. Here we detail 18 of the most essential tools that work well with Hadoop.
KDnuggets talks with Anjul Bhambhri, IBM’s Vice President of Big Data Products about Big Data Trends, developing the Big Data capabilities in-house vs. outsourcing, five crucial steps to adopting a success big data strategy and advice for beginners.
Good #BigData summer reading list; Data Mining and Rap? Jay-Z’s new album is a massive data-mining operation; 7 #BigData Definitions, also: Data is Big when its size becomes part of the problen; Search theory and #BigData: Applying Bayesian math that sank U-boats to intelligence