Big data is a popular topic these days, not only in the tech media, but also among mainstream news outlets. Executives see Big Data as providing significant business benefits – greater insight and learning, the ability to obtain answers and make decisions faster and in a more informed manner, greater agility and flexibility.
Big data is hence a major business issue and Hadoop is the platform that makes big data easier to manage. Especially after April’s official release of big data software framework, Hadoop 2.7.0 is generating even more media buzz.
Analytics for Hadoop can be done by the following:
- Writing custom Map Reduce code using Java, Python, R ..etc
- Using high level Pig scripts
- Using SQL using Hive
Hadoop is a being recognized as a vital constituent of BI
Industry studies reveal that Hadoop products like MapReduce, Java, Pig, HDFS, Hbase and Hive have gained a strong popularity.Other products like Mahout, Zookeeper and Hcatalog would be getting on real shortly.
Professionals who have learnt Hadoop have now started integrating Hadoop with DW’s, analytic tools, web servers, data visualization tools, reporting tools and analytic databases. Big organizations across the world are witnessing a spurt in their data volumes and this is a chain reaction that is unstoppable.
Hadoop has a cutting edge over traditional RDBMS
Hadoop is scalable: Hadoop is highly scalable and is designed to store and distribute huge data through multiple servers operating in parallel.
Hadoop is inexpensive: When it comes to data explosion, Hadoop has established itself as the most inexpensive storage solution. When it comes to processing massive amounts of data, scaling of traditional RDBMS’s proves extremely expensive.
Hadoop is Flexible: This is another compelling reason as to why a BI professional should learn Hadoop. Be it social media, clickstream data or email conversations, Hadoop has the ability to derive useful data from all types of data resources. Further, Hadoop can be efficiently used for recommendation systems, marketing campaign analysis, fraud detection and data warehousing as well.
Hadoop is fail proof: When using Hadoop, data sent to an individual node also replicates on all the other nodes in the cluster, so in case of failure on one node, there is always a backup copy of the data available in the cluster.
Why choose Gloify as your technology partner for Hadoop development?
Gloify focuses aspects that have greater impact on the results while simplifying the process of Hadoop inculcation. We follow a simple process and make it clutter-free for your organisation.