Hadoop Data Lakes: Three Ways to Get Data Where You Want

by Digital Education thought and bren

In today's world, data or digital information is an essential factor for business growth and this data is increasing exponentially. To handle and manage this growing data, many software known as relational database management system (RDBMS) and the associated hardware to support these software are frequently used by the corporate which burdens these organizations financially.

Organizations are looking for a solution which can handle the vast amount of data without interfering with their traditional data warehouses. Hadoop Data lake is the need of the hour as this concept can include other types of system and store a diverse mix of structured, unstructured and semi-structured information for big data management and analytics applications.

Why are organizations opting for Hadoop?

There are mainly two reasons for using Hadoop for data management and analytics and these are:

• Cost-effectiveness

Hadoop is an economically efficient data platform because of the cost of the software and support like commodity hardware, per node or CPU, is significantly cheaper than other RDBMS. The reason of this cost reduction is that you need not worry over common things like redundant power supplies or disks since redundancy is an inbuilt feature in the system with Hadoop. It means you can easily upgrade memory on nodes independent of the software licenses and other formalities. This feature of Hadoop prevent the burdening of IT budget and also make it predictable.

• Improved efficiency

Besides being a cost-effective Data management system, it also has greater efficiency than other expensive RDBMS. This data platform can easily handle the exponentially growing unstructured and semi-structured data. Moreover, data can be loaded independently of format and structure, unlike other RDBMS which means that there will be no delay in data availability to the clients or consumers. The new data can easily be moved into Hadoop and exposed to the masses without any big effort or time lag.

Three Ways To Use Hadoop To Get Data Where You Want It To Be

Use Hadoop as a new data store

Hadoop can easily handle raw data (unstructured data, semi-structured data or unanalyzed data) which is not yet subjected to Enterprise Data Warehouse (EDW). It doesn't interfere with the existing data warehouses but allows them to fetch data from it. A small group of users can work on this for analytics purposes.

Use Hadoop as input provider for the EDW and source for analytics

Any new useful insights found in the new type of data stored in Hadoop can be fed into the EDW to expose it to the masses. Organizations can use Hadoop to dig new valuable data and get benefited by providing it to the masses. Although it doesn't impact the EDW much the inflow of new data into the EDW make it grow.

Use Hadoop for BI and analytics.

organizations are using Hadoop as the main source for business intelligence (BI) and analytics. Sometimes data from Hadoop is directly used and sometimes the data is pre-processed at other RDBMS or other data storage and then used with Hadoop.

Hadoop data lakes are very useful when a vast amount of data need to be pooled. The above three use cases of Hadoop also utilizes the data lakes and provides the data to the end user effectively.

All these features of Hadoop have made it a new sensation in IT industry and Companies are looking for trained professionals so that they can implement it in their organizations at earliest to reap its benefits. Many training institutes have realized the need of the hour and offer big data Hadoop training courses.

If you are also looking for a Hadoop institute to enhance your IT skills then deducation is the perfect place to start your IT career. D-Education is Hadoop training institute in Gurgaon which offers big data Hadoop training course . The facility is well equipped and students are trained by the experienced and expert team so that you can get the best knowledge of the IT industry. Come join us for a bright career!