Hadoop technology

1.        The advantages that are associated with Hadoop and technology and distributed data file systems; include the fact that it promotes scalability regarding storage platform as it can store and distribute large data sets across numerous of inexpensive servers operating in parallel (Zikopoulos & Eaton, 2011). Hadoop further offers more cost effective storage solutions, promotes the ability of businesses to easily access data sources as well as tap into divers’ forms of data and fault tolerant. The fact that Hadoop’s storage method is dependent on a distributed file systems that can map data wherever it is located in the cluster. The attributes make it possible for businesses dealing with large volumes of unstructured data to efficiently process it fast.

2.        Hadoop is different from the RDMS in that it scales large amounts of data, allowing businesses to run applications on thousands of nodes that entail numerous terabytes in addition to the fact that it is more cost effective as a storage solution for businesses (Bao, Ren, Zhang, Zhang, & Luo, 2012).

3.        The organization issues that are addressed via the use of Hadoop include the huge data storage needs, mostly that the ones that are data driven as the healthcare sector. In the financial industry, the Hadoop technology has been promoting the operational margins as well as detects malicious activities that could be unnoticed in the ordinary scenarios (White, 2012). These types of data that are analyzed include data records, re-occurrence of heart attacks as well as the anti-money laundering practices.

4.        The companies that are currently Hadoop technologies include Amazon, Cloudera, Hortonworks, IBM, Datameer, Oracle and Teradata.

References

Bao, Y., Ren, L., Zhang, L., Zhang, X., & Luo, Y. (2012, July). Massive sensor data management framework in cloud manufacturing based on Hadoop. In IEEE 10th International Conference on Industrial Informatics (pp. 397-401). IEEE.

White, T. (2012). Hadoop: The definitive guide. " O'Reilly Media, Inc.".

Zikopoulos, P., & Eaton, C. (2011). Understanding big data: Analytics for enterprise class hadoop and streaming data. McGraw-Hill Osborne Media.

Sherry Roberts is the author of this paper. A senior editor at Melda Research in best nursing writing services if you need a similar paper you can place your order for custom nursing papers.