Managing Unstructured Data Using Hadoop

Generating unstructured data very quickly is one of the motivational powers of the new big data analysis model. Mostly the data created is of unstructured variety and up to 90% data created is unstructured.

Big data is used to collect the unstructured data as well as combine it with other data types. This helps to get new insights which can further be used to advance business performance. Let’s understand this with an example:

When we consider retail sector, it means we should provide proper customer service which is fast as well as reliable. While in case of research, it means performing experiments with various samples and when considering health care industry, this means accurate and quick diagnosis for every illness.

Big data plays an important role in transforming our lives especially for those who need to collect and combine various data thus to get answers of all their long questions. Organizations must have proper technology to store huge unstructured data in its original form as this will help big data to show its entire potential in an effective manner. Here, Hadoop plays an important role. So, let’s understand what exactly Hadoop is and how unstructured data can be managed easily with it.

Hadoop is one of the most enabled data processing technologies used for analysis big data and it permits as well as provides answers to every question of the huge business enterprises. This can be easily seen from well known large cloud companies which will soon sneak in to other IT services as well as industries.

As per a survey, over 50% of the companies have started using Hadoop frameworks to store their data and it is also used as minor data depository for their current infrastructure. Here, we have mentioned some of the key characteristics of Hadoop that make it popular:

Cost Effective Technology:

Hadoop runs on standard servers. Hardware can either be added or exchanged inside the group. The operational costs for Hadoop are relatively very less as compared to other data management software frame works.

Large Data Sets can be Processed Easily:

One of the Hadoop’s programming framework – Map Reduce is used to process data sets in a very quick and efficient manner. It helps users to easily organize the data in various groups of computers and the complex data structures can be easily processed.

Supports Current Database and Analytics Infrastructures:

Some data is very sensitive which legal databases fail to handle. Such databases can be easily handled by Hadoop. While selecting any big data storage, care must be taken that storage is capable of handling the capability and speed of big data initiatives.

With these and some other characteristics, it is sure that Hadoop is the perfect open source software framework used to manage unstructured data that is increasing rapidly across all applications in different formats

This is the reason why 80% of companies are taking benefits of Hadoop and so you should be the one among them.