Big Data: How Big MNC’s store, manipulate, and manage data.
Tags: Hadoop, Distributed Systems, Data, Big Data, Mnc

Ever wondered why all the big MNC’s like Facebook, Instagram, YouTube, Netflix have such a huge amount of data, or how it is stored, what are the problems they face with this huge amount of data, and what they are doing to deal with these problems. Let’s try to find some of the answers in this article.

What is Big Data?

Before diving in let’s first know about the word ‘data’ around which the whole world is moving so, Data are the facts which can be in the form of images, videos, statements, etc. which give information about something or someone.

Now let’s know Big Data, in simple words, we can say that Big data is data but with huge size. It is larger, more complex data sets, especially from new data sources, and is growing exponentially with time. These data sets are so voluminous that traditional data processing software just can’t manage them.

Big data is characterized as volume, value, and velocity, known as 3Vs, these are also problems faced in big data.

Volume: Huge amount of complex data is being generated each day by companies and storing such a huge amount of data becomes a challenge as it can no longer be saved or analyzed using conventional data processing methods. examples of some MNCs producing data daily.

Huge amount of complex data is being generated each day by companies and storing such a huge amount of data becomes a challenge as it can no longer be saved or analyzed using conventional data processing methods. examples of some MNCs producing data daily. Velocity : It is the speed with which the data is generated, analyzed, and reprocessed. Today this is mostly possible within a fraction of a second, known as real-time.

: It is the speed with which the data is generated, analyzed, and reprocessed. Today this is mostly possible within a fraction of a second, known as real-time. Variety: Data comes in all types of formats — structured, Semi-structured, and unstructured such as text documents, emails, videos, audios, stock ticker data, and financial transactions.

MNCs need a large amount of data despite so many challenges because Big data databases help to save companies money, grow their revenue, and help to achieve other company objectives.

How to solve a Big Data problem?

One way to solve Big data is to use a Distributed Storage System. A distributed storage system is the infrastructure that can split data across multiple physical servers, and often across more than one data center. It is also used for high availability, data backup, and disaster recovery purposes.

One example of a Distributed Storage System is master-slave topology. In this system, lots of storage resources are connected to the one main master storage. This master node is known as the Name node and the slave storage nodes are known as the data node. All these data nodes provide their storage to the one single master node. With the help of this system, we can solve both the volume and velocity problem without spending on physical storage.

For the Implementation of a Distributed storage concept, there are many software's in a market like Apache Hadoop.