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7 Best Practices to Get Started With Hadoop in Your Organization

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7 Best Practices to Get Started With Hadoop in Your Organization

In this post, we look at the benefits that Hadoop brings to big data teams and how organizations can go about integrating Hadoop into their workflow.

· Big Data Zone ·
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Enterprises are always looking for ways to extract business value from their data. They have shifted their focus on analytics as the primary source of getting this value.

This is where Hadoop benefits the businesses as it is not only efficient in handling large data volumes but also very affordable. With its help, even the small scale organizations can scale their existing IT systems.

Due to this reason, it is expected that the usage of Hadoop is going to increase significantly in the upcoming years. In fact, according to a survey conducted by TDWI, it was found that the number of Hadoop clusters has increased by more than 60 percent in the last two years.

What Is Hadoop?

Hadoop is a software library which allows for the storing of big data sets in a distributed system and the processing of these data sets in clusters with the help of simplified programming modules.

The different modules of Hadoop include:

  • Hadoop Common - The module which supports the different components of Hadoop.
  • HDFS - Creates an abstraction and helps in accessing the stored applications and data faster.
  • YARN - Helps in managing and scheduling the resources and jobs in clusters.
  • Map Reduce - Based on the YARN system which helps in parallel processing of big data.

Benefits of Hadoop for a Business

If you are not one of the companies who has integrated Hadoop into their production environment, then you are missing a lot. The enterprises who are using it have nothing but positive results.

The international Hadoop market is expected to earn a revenue of more than $50 million by the end of 2020. Therefore, there is no more perfect time than now for businesses to start using Hadoop

Economical and Scalable

As compared to other software solutions, Hadoop is very affordable and cost-effective. It is very scalable because it can easily distribute large data sets over inexpensive servers.

In traditional and rudimentary solutions, you cannot scale without investing some amount of money from your budget. Most businesses delete the raw data and keep the important ones to cut down the processing costs.

While it is beneficial in the short term, you will face difficulties in the future if you want to use this raw data for achieving different objectives.

With Hadoop, you don’t need to delete the raw data as it provides several features which you can use to scale your business.

Versatile

Hadoop allows enterprises to access new data sources and other various data sets. The varied data sets help enterprises to get the maximum advantage of the large data repositories.

An example of the flexibility and versatility of Hadoop is its power to access social networking sites such as Facebook, Instagram, Twitter, and others for gathering a large amount of valuable information.

If the data and information are used appropriately, then it will be of great value for an enterprise to reach its full potential.

Speed of Processing

Hadoop can easily map any data on a cluster in the enterprise's server. The tool which is used by Hadoop’s storing system and the data are on the same server; therefore, it allows for fast processing and retrieval of data and information.

With the help of Hadoop, you can also process the unstructured data within a couple of minutes. Hadoop’s high-speed processing makes it a better choice than the other options available in the market.

Secure and Future Proof

Hadoop provides comprehensive security for any business or enterprise. Its security parameters do not allow any unauthorized access from outside. It works as a shield and warns you if there is any unwanted access to the system.

Whenever you store a piece of particular information or data to a specific node of the cluster, it is copied in the other nodes as well.

Therefore, when one of the nodes gets crashed or destroyed, you can always access your data from the other nodes.

Best Practices to Integrate Hadoop in an Enterprise

As you are now aware of the benefits of Hadoop, let’s look at the best practices you should follow to integrate it into your organization.

These are seven best practices which are applicable for both the small and large organizations.

Define Usage

The very first thing you need to do is define the initial usage of Hadoop. You might have thought of building a huge data bank, but it is advised to, instead of starting big, have small and achievable goals which will help you in data processing.

Start by defining the data access and the different types of data users needed, along with the ways to access the data such as data extracts, prepared reports, visualizations, etc.

You have to use different data extraction methods for defining each and every boundary.

Use Existing Enterprise Frameworks

The best thing about IT is that you don’t have to invent new methods and techniques. There are plenty of libraries and frameworks available which can help you to adopt Hadoop into your system.

Therefore, use the frameworks that monitor the functions for data access, communication, etc. Some of these frameworks include Spring, JAX-RS, and others.

The benefit of these types of frameworks is that developers do not need to spend their valuable time on the control processes; instead, they can use it for business logic and strategizing new methods to scale their business.

Data Quality

The quality of data is very important in Hadoop development. If your system is monitoring the management tools, then the Hadoop development should also work along with the tools for capturing the bids in case of exceptions.

You can also implement the data reconciliation frameworks to handle any data quality problems.

Data Modeling

As Hadoop can store any type of file, many developers just throw data at it and expect optimal processing performance.

This is not the best way to process data; instead, you need to tailor data modeling according to their patterns. You also need to understand whether the data is exploited in data formats or data access methods.

Data Lineage

As the data sets grow, you need to track the data lineage. You can perform this by adding metadata to the incoming data.

There are several advantages and Hadoop you helps to track the data quality and elements directly from the source to the destination. You can also assign data access rights and catalog different data sets in Hadoop clusters.

Security

Although Hadoop is highly secure, you need to follow the guidelines for the best usage. Use directory-based security such as Active Directory and LDAP which makes it very safe and manageable.

Apache Sentry helps in enforcing the security of the metadata in Hadoop clusters. For more granular security, you can select virtual approaches to the data sets.

The Final Say

As technology and businesses across the globe are continuously evolving, the adoption of Hadoop is also increasing significantly.  

It is just the beginning, and in the upcoming years, both small scale and large organizations will incorporate it into their systems.

All you need to do is follow the best practices listed above to get its maximum benefit.

Topics:
big data ,apache hadoop ,hadoop beginner's guide

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