Hadoop was developed to cater to the needs of web and media companies for managing big data. But even if you don’t have to deal with big data, you can still use Hadoop in many ways to enhance your data and resource management. Today Hadoop is being used by almost every business, whether they have big data or small, to manage their data.
The Main Features of Hadoop:
MapReduce was developed for resource management and data processing but with Hadoop 2.0 it has been left just to focus on data processing while YARN is used for resource management.
These features of Hadoop can be utilized in many innovative ways by big and small businesses.
One straightforward use of Hadoop is to archive data files. Since HDFS runs on commodity hardware it is simple and cheap to scale so businesses can start small and expand as their business grows. They can store all their data at a very low cost.
Instead of destroying data after the regulatory period is over, companies can store decades of data and analyze it in real-time to help their decision-making process.
Data Staging Area:
Traditionally ETL tools are used for extracting and transforming data. When Hadoop came to the scene, it could have killed ETL forever if ETL providers hadn’t been smart enough to provide HDFS connectors so that Hadoop could be used along with their ETL software.
By using Hadoop you can store the application data and the transformed data in the same place. This makes it easier to process the data at a later time and reduces the time to process the data. Hadoop can help ETL in improving data processing.
Instead of sending data to the warehouse and then use costly resources to update it in the warehouse, you can use Hadoop and its MapReduce function to process and update it before it goes to the warehouse. Hadoop’s low-cost processing power can be used not just for your warehouse data but for other operational and analytical systems as well.
Hadoop is a very powerful tool that can help all businesses to handle their data in a better way. You don’t have to be sitting on top of big data to using Hadoop. You can start even when you have small data and Hadoop will let you collect decades of data till it becomes big data and then you can start making use of all this data by using big data analytics.
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