Discuss The Role of Hadoop in Supporting Big Data Initiatives Essay:
Hadoop is widespread open source software used in storage and processing of large sets of data in a distributed business environments (Prajapati, 2013). The notion behind the development of Apache Hadoop software is that, the failure in hardware especially on personal computers and servers holding large volumes of digital data is very common thus a need to automatically handle the Big Data in a software framework. The unique approach of Hadoop software has transformed how institutions collect, store, analyze, use and distribute their Big Data. The common Big Data initiatives have included new methods to capture, search, share, transfer, use as well as information security and privacy. More advanced initiatives in Big Data have involved extraction and manipulation of raw data to help organization make accurate and more confident decisions that will guarantee improved operational efficiency, reduced business costs and risks.
Notably Hadoop software is gaining much attention and adoption in organization that are dealing directly with huge volumes of data such as IT companies as well as online data backup providers. The need for Big Data in analytics, business intelligence and decision making has enlisted the endless needed support from Hadoop software (Kudyba, 2014). Data analytics has become a vital component in organization that need to efficiently use the information to stay competitive and gain markets in new areas. On the other hand, business intelligence is widely using Big Data to plan and forecast market changes and proposes new methods to stay afloat in the competition. Additionally, Big Data is becoming more and more critical in decision making thus a need for dedicated platforms such Hadoop to support organizations that utilize this information for the benefit of the organization.
References
Kudyba, S. (2014). Big Data, mining, and analytics: components of strategic decision making. Boca Raton: CRC Press
Prajapati, V. (2013). Big Data analytics with R and Hadoop. Birmingham: Packt Publishing Ltd
 
 

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