What is Big Data Hadoop and Its Importance in 2021

 

Big Data Hadoop and Its Importance

It is nearly impossible for organizations to function without data in today’s data-driven world. Data is an asset and allows businesses to perform smoothly. Also, the coronavirus pandemic has forced millions of employees to work from home. All this has made it essential to have cost-effective and efficient tools for data storage and processing.

What Is Hadoop?

Hadoop is an open-source platform by the Apache software foundation. It can store and process large amounts of data in a distributed environment through simple programming models.  It can easily scale up from single servers to hundreds of computers, with each computer offering local storage and computation. It is a flexible resource that quickly processes large enterprise-level data sets.

Hadoop has many components that help it to function. So, when you join any Hadoop Training Course, make sure they are included in your course curriculum. These components are listed below.

Components of Hadoop Ecosystem

·         HDFS - Distributed File System (HDFS) is the storage component that stores data in the form of files. The file is then divided and stored on different machines in the cluster.

·         MapReduce - MapReduce is the processing unit that divides a single task and then processes them individually to reduce traffic on the network.

·         YARN - Yet Another Resource Negotiator is the resource management unit.

·         HBase- It is a Column-based NoSQL database that can handle any type of data.

·         Pig- It analyses large datasets and helps write maps and reduce functions.

·         Hive- It is a distributed data warehouse system that allows for easy writing, reading, and managing files on HDFS.

·         Sqoop- It plays a vital role in bringing data from Relational Databases into the HDFS.

·         Flume- It is an open-source service used to efficiently aggregate, collect and move large amounts of data from different sources into HDFS.

·         Kafka- Kafka connects applications generating data and the applications consuming data.

·         Oozie- Oozie is a workflow scheduler system that links jobs on platforms like MapReduce, Hive, Pig, etc.

·         Zookeeper- It is an open-source, centralized, and distributed service that coordinates and synchronizes clusters across HDFS.

Importance of Hadoop

Big data analytics is the processing and understanding of large datasets to uncover hidden meanings in them. Hadoop is an important technology for big data analytics for many reasons. And this is why most of the data science bootcamps offer Hadoop courses for specialized training in Hadoop. Several reasons make Hadoop imperative to learn. Some of them are mentioned below.

Quickly stores and processes data

Data comes from different sources like web servers, Internet clicks, social media posts, emails, mobile apps, and sensor data from the IoT. This data may be structured, semi-structured, or unstructured. Hadoop can store and process vast amount of data at a faster rate.

It can efficiently process terabytes of data in minutes and petabytes in hours. It uses a unique distributed file system to ‘map’ data on the cluster it is located. Faster processing is possible because the processing tools are located on the same server on which the data is collected.

Flexibility to store varied data

It’s said that only 20 percent of data is structured, and the rest of it is unstructured. Therefore, it is very crucial to manage unstructured data that is difficult to manage. To store a variety of data, traditional methods are not successful. This is especially true for unstructured data. Moreover, with the help of the MapReduce technique, all kinds of data can be managed.

Hadoop can handle various types of data, whether structured, coded/formatted, or unstructured. It can support any kind of programming, especially Java programming. Also, Hadoop can work on any operating system such as Windows and Linux, BSD and OS X, etc.

Protects and secures data

Hadoop has a critical role to play in protecting the data against any hardware failures. It stores data in the nodes, so whenever a node gets down, it redirects the processing to other nodes ensuring the application runs smoothly. Likewise, the data stored in HFDS is encrypted in a secure application making Hadoop a popular option.

Scalable solution

By the year 2025, the global data is expected to hit more than 180 zettabytes. This suggests the need to have scalable storage solutions that would be capable of handling such big data. Hadoop can run on any industry-standard hardware. Also, it is possible to add new nodes in its system as and when needed without changing the data format or existing applications.

Career with Hadoop

Choosing the Best Big Data Hadoop course can make a big difference to your career if you want to make it big in the data analytics field. If you are trained and certified, it will be easier for you to keep up with the current trends and changing markets.

Hadoop skills are in great demand because the amount of data generated every day is increasing at an extraordinary pace. And, to manage this data, companies are planning to shift to big data analytics.

The market forecasts also look promising. So, today is a great time to invest in the best Hadoop course in California. Hadoop training can offer tremendous job opportunities in this growing sector.