ProjectPro

NOVEMBER 7, 2014

A good hadoop big data resume might not be enough to get you selected but a bad hadoop big data resume is enough for rejection.Many big data professionals consider writing big data hadoop resume as an exercise in psychological warfare. Are you one among them? Do you want to move your big data hadoop resume from the slush pile to the "YES" pile ,then you must follow some important guidelines to ensure that your hadoop big data resume does not land into the "NO" pile of CV's.This article aims to p

Technology

ProjectPro

NOVEMBER 24, 2014

With a rapid pace in evolution of Big Data, its processing frameworks also seem to be evolving in a full swing mode. Hadoop (Hadoop 1.0) has progressed from a more restricted processing model of batch oriented MapReduce jobs to developing specialized and interactive processing models (Hadoop 2.0). With the advent of Hadoop 2.0, it is possible for organizations to create data crunching methodologies within Hadoop which were not possible with Hadoop 1.0 architectural limitations.

Hadoop

ProjectPro

NOVEMBER 11, 2014

Confused over which framework to choose for big data processing - Hadoop MapReduce vs. Apache Spark. This blog helps you understand the critical differences between two popular big data frameworks. Hadoop and Spark are popular apache projects in the big data ecosystem. Apache Spark is an improvement on the original Hadoop MapReduce component of the Hadoop big data ecosystem.

Hadoop

ProjectPro

NOVEMBER 5, 2014

Hadoop is the way to go for organizations that do not want to add load to their primary storage system and want to write distributed jobs that perform well. MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets. For organizations to keep the load off MongoDB in the production database, data processing is offloaded to Apache Hadoop.

MongoDB

Speaker: Jason Chester, Director, Product Management

In today’s manufacturing landscape, staying competitive means moving beyond reactive quality checks and toward real-time, data-driven process control. But what does true manufacturing process optimization look like—and why is it more urgent now than ever? Join Jason Chester in this new, thought-provoking session on how modern manufacturers are rethinking quality operations from the ground up.

Manufacturing