Hadoop is the new sensation when it comes to Big Data Management. The rate at which it is gaining popularity is massive. Of course, there are plenty of tools and techniques available to manage and provide vital insights from Big Data. But no other technology is capable enough to offer expected results as quickly and as efficiently as Hadoop does. So, let us look at the things which put Hadoop first in the list of data handling tools and why big data analytics training is essential for your career growth.
Reasons why Hadoop is the best for data handling?
Scalability
The versatility level of Hadoop is exceptional. It can store and manage an extensive amount of data from several servers and parallelly process them. You won’t get this versatility in any other traditional database systems and even in other modern competitors with such efficiency. It can handle the massive amount of data in terabytes and provides the output very quickly. Further, it gives a lot of flexibility to the business of all sizes.
Fast
Hadoop produces the results in very little time compared to other data processing tools. It is possible in Hadoop because it comes with a unique storage system with a distributed file method, it maps datasets on the cluster. And usually, the tools of data processing are located on the same server, it also fastens the processing speed and produces the results quickly. Especially if you are dealing with vast datasets of unstructured data, it handles the terabytes of data in a matter of a few minutes and petabytes in hours. All these reasons compel a developer to take big data online classes to gain a competitive advantage.
Inexpensive
Hadoop has a significant advantage when it comes to cost. It enables businesses to get the best storage solution to handle large data sets. The main problem with traditional tools to manage the data is the cost; with the increasing volume of data, the business has to spend more money, but thankfully, it saves from this problem. Since the price was higher, many companies used to classify some data sets purely based on assumptions and analyze it. With Hadoop technology, all types of data, whether large or insignificant, you can process and analyze it before it used to cost from one thousand to ten thousand dollars to process each terabyte. Now Hadoop reduced the cost significantly so the business can get the insights of a terabyte of data by spending in hundreds. Even if you want to learn Hadoop, you don’t need to pay hugely. Hence you can complete Hadoop training online by spending less.
Fault Tolerance
One of the top reasons businesses should opt for Hadoop instead of others is its unique way of handling failures. In this platform, once data is sent to anyone node, it replicates the same data and stores them in the other nodes in the cluster. In short, what it implies is, if any one of the nodes gets failed, the data saved in other nodes makes it available to use. It may look like the drainage of memory, but it gives a great advantage when the system encounters failures. The MapReduce component available in the Hadoop ecosystem goes beyond this by eliminating Name Nodes and replacing them with distributed no Name Nodes, which offers excellent data availability.
Adaptability
The problem of every company is the type of datasets they need to analyze. Nowadays, many organizations produce a considerable amount of data in both structured and instructed data types. And to manage the different kinds of data Hadoop is an efficient tool. That means companies can benefit from obtaining vital insights from various data sources, including email discussions, online networking, clickstream details, etc. Additionally, the Hadoop ecosystem can be used for several purposes, including proposal frameworks, log preparing, information warehousing, fraud detection, marketing insights, etc.
Without a doubt, Hadoop is equipped with all the necessary tools to handle and produce the output every business is looking for from all data types. With the increased benefits and demand for Hadoop professionals, anyone can learn mastering the Hadoop system by enrolling in any Hadoop training online.
