Big Data Hadoop: What Are the Core Features?

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Hadoop is a well-known non-proprietary software for big data analysis. It is essentially applied in the industries in sophistically storing and processing large datasets, which have a size range between gigabytes and petabytes. Instead of utilizing one centralized computer for the analysis of data, the software supports the assimilation of multiple computers that analyzes the data simultaneously. In particular, the software renders the users easy and comprehensive utilization of processing and storage capacity in the clusters of computers. Furthermore, the software also enables the users to implement distributed processes when dealing with a huge amount of data. Moreover, it provides fundamental blocks using which the developers can build utility services and applications. It is a coveted career field because of the widespread demand in the industry and thus Big Data Hadoop Online Training in India has become prominent in recent times.

Now, let us proceed ahead and read about the notable characteristics of Hadoop in the subsequent section.

Features of Big Data Hadoop

The intuitive features of Hadoop have made it a ubiquitous, reliable, and robust tool for big data analysis. Proceed to the subsequent pointers to peruse the notable features of the software:

Open-Source:

The open-source nature of Hadoop makes it a streamlined software to use. Furthermore, it also means the source code is available online, and that makes it a cost-efficient solution as well. Anyone can configure modifications and understand the source code anytime through the internet.

Scalable Cluster:

The high scalability of Hadoop essentially allows programmers to fragment large datasets into small virtual computers in the form of a cluster. This cluster is then processed comprehensively in parallel. This is to ensure accurate and comprehensive data analysis.  Now, the total number of virtual machines in the cluster can be raised or decreased. Users can scale up or down the cluster pertaining to the business requirements.

Fault Tolerance:

Hadoop offers optimal backup because it copies all the data in DataNodes, which is available in the cluster. Thus, your data remains safe even if some of the systems malfunction. Thus, if one of your systems containing the data stops working, you can proceed to access the data from other DataNodes. The copy and storage of data are automatic, but you can also create three copies of each block and then store them in distinct nodes.

Conclusion

Data has become a non-negotiable aspect of our lives and multitudinous industries domestic and worldwide depend on it.  Thus, the dependency on robust analysis of such complex data increases. Thus, the need for sophisticated big data analysis software is on the rise. This is because a copious amount of data is being generated on a daily basis. Therefore, the job prospects and growth in the domain involving Hadoop have seen an incremental change in recent times. However, a comprehensive skillset, background in data analysis, and valuable certification course from Big Data Hadoop Training Institute in Noida are crucial for success in this field. Choose a reputable institute and select online or classroom modes of learning as per your needs. The growth in this domain will evolve fast in the future. Therefore, now is the time to leverage profitable opportunities available in the market.

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