Why you Should Include Hadoop in your Big Data Strategy
With the emergence of Big Data, there is an urgent need to collect and preserve whatever data that is being generated. Because there is a large amount of data floating around, Big Data Analytics has become crucial, and it aids in decision making, improving business and productivity for both organizations as well as individuals.
If you have been working on a big data strategy, you might be aware of Hadoop, an open source framework that supports processing and storage of a large amount of data. Hadoop has emerged as a leading framework for big data analytics. This framework was successfully adopted by companies such as Twitter, Yahoo, and Facebook to deal with their big data challenges. It brings with it many benefits that make it the most convenient platform while working on a big data strategy.
Below are some advantages of using Hadoop in your Big Data Strategy!
For organizations, there is an ocean of opportunities in the Big Data Analytics domain and including Hadoop in your strategy will be beneficial due to its following features:
One of the main reasons why companies prefer to adopt Hadoop is due to its low cost of implementation. While choosing a data management system, cost effectiveness is a major factor to be considered. Hadoop can handle big data sets efficiently without having to spend on storing a large amount of data as with this it is possible to use all your data without having to delete the unwanted data. There is no need to spend a large amount of money based on the terabytes of data to be stored.
Hadoop is one of the most scalable data storage platforms that any organization can invest in. With this framework, you can start with a single server and grow and distribute data to provide computation and storage for up to thousands of machines or servers. This enables you to run your applications carrying terabytes of data smoothly on thousands of nodes and servers.
The biggest issue when using traditional methods of data management is to deal with lagging and sluggish system. Hadoop offers a distributed file system for data storage that facilitates the rapid transfer of data among nodes and enables systems to run smoothly without much interruption. The distributed file system maps the exact location of data on the server and hence leads to faster data processing. It lets you process a large amount of data efficiently within minutes.
Flexibility of Data
Hadoop is designed for the storage and processing of both structured and unstructured data. This means you will be able to use different data types and drive business insights from data sources like social media, email conversations, and clickstream data. The flexibility feature of Hadoop lets you use it for market campaign analysis, log processing, fraud detection and data warehousing.
Less Prone to Failure
Hadoop has higher tolerance and resistance to fault when compared to other platforms. It is because of the way it works. When data is sent to a node, it is replicated to all the other nodes in the cluster and hence there will always be a copy of the data available, which means a lesser possibility of failure.
Hadoop provides advanced analytics with more accurate figures and facts than other platforms. It also offers additional features like data analytics and predictive analysis of data which gives insights in a graphical manner. When it comes to dealing with large volumes of information, Hadoop is safe and reliable as compared to traditional data management systems.
Hadoop lets you collect and keep all your data in a well-organized manner. With all these advantages, small and large businesses should definitely include Hadoop in their big data strategy. If you are looking for a suitable big data analytics strategy for your business, Semaphore Software is an ideal pick. We follow a unique approach to helping you make meaningful decisions based on critical analysis of data. Write to us at firstname.lastname@example.org for all your big data requirements.