Big data analytics would not probably be what it we know it to be today unless for Hadoop. It might sound like an overstatement but it is not. Different industries around the world are still in the process of understanding and utilizing the real value of data. There can be no doubt however that the world of commerce has come a long way in terms of implementing data analytics. And Hadoop software suit deserves a fair share of credit for this development.
Hadoop solved a key problem which is data storage
The process of data creation is an automatic one; most of us participate in this process without even realizing. The sheer number of people, who use various digital mediums to go by with their lives, is the key contributor to the humongous amount of data that is around today. A considerable portion of this information carries the possibility of leading to some crucial insight which might lead to some ingenious development in the policies of a company, business processes and various metrics in the production line. The point is that one cannot just dispose this data off without surveying its potential.
This leads to two problems
- It requires special tools to manage such huge amounts of data.
- Attempting to store the data costs a fortune.
Hadoop relieved the enterprise owners from this headache regarding data storage. The Hadoop distributed file system (HDFS) introduced distributed file storage. In simple terms, this joins a cluster of commodity servers. It works on multiple machines at the same time. The storage capacity can be increased by increasing the number of servers.
This does not only increase the efficiency but also reduces the costs. This cost-effective solution is used by 14% of the companies that implement data analytics.
A significant number of firms operating from Bangalore use data analytics and therefore use Hadoop. Undergoing big data Hadoop training in Bangalore can open a door or two for you.
Democratizing Big data with Hadoop
We have already talked about the overwhelming costs of managing big data with the traditional tools. Big data was the prerogative of large corporations whereas it is more important for the new companies or small enterprises to utilise data driven insights to develop business. Hadoops storage unit HDFS and processing unit MapReduce democratized the process of big data analysis owing to their open source nature and cost-effective model. The super fast data processing tool Spark has somewhat supplanted MapReduce, nevertheless it works in a Hadoop ecosystem hence Hadoop’s relevance is not harmed if not enhanced.
Hadoop skills are in high demand
Hadoop development and administration are not easy tasks. The learning curve is a steep one. Not everyone can work in a Hadoop ecosystem with ease. It requires well-focused training to prepare a person as a Hadoop professional; consequently the employers always watchful for capable minds. Quite obviously it keeps the salaries quite high.
Enrol for Big data Hadoop training in Bangalore in order to be equipped with the highly sought after skills which have defined the field of analytics for so long.