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Big Data is a term for collection of data sets so large and complex that it becomes difficult to process using hands-on database management tools or traditional data processing applications. Let us talk more about this in this article on Introduction to Hadoop.
Big Data has now become a popular term to describe the explosion of data and Hadoop has become synonymous with Big Data. Doug Cutting, created Apache Hadoop for this very reason. Hadoop has now become the de facto standard for storing, processing and analyzing hundreds of terabytes, and even petabytes of data. Hadoop allows distributed parallel processing of huge amounts of data across inexpensive, industry-standard servers that store and process data.
The above video is the recorded session of the webinar on the topic “Introduction to Hadoop”, which was conducted on 8th August’14.
Here are some use cases of Big Data in Retail, Banking and Financial sectors:
Banking and Financial Services:
This video includes a case study where the usage of Hadoop by Sears has been discussed. Sears was previously using traditional systems such as Oracle Exadata, Teradata and SAS to store and process the customer activity and sales data. On adapting Hadoop, Sears gained valuable advantages like :
The video has a step by step explanation of the flow of data and limitation faced by it in existing data analytics architecture and how Hadoop over comes it. Hadoop provides a solution where a combined storage computer layer is utilized. As a result, Sears moved to 300 node Hadoop cluster to keep 100% of its data for processing rather than the meager 10% that was available in the existing non-Hadoop solutions.
Moving on with this article on Introduction to Hadoop, let us take a look at why move towards Hadoop.
The following reasons make it pretty clear as to why one must move to Hadoop.
“We’ve heard it’s a fad, heard it’s hyped and heard it’s fleeting, yet it’s clear that data professionals are in demand and well paid. Tech professionals who analyse large data streams and strategically impact the overall business goals of a firm have an opportunity to write their own ticket.” said Alice Hill, Managing Director of Dice.com.
As per the 2012-13 Salary Survey by Dice, a leading career site for technology and engineering professionals:
Moving on with this article on Introduction to Hadoop, let us take a look at the Hadoop ecosystem and its architecture.
Hadoop comprises of two main components:
HDFS – Hadoop Distributed File System – For Storage
MapReduce – For Processing