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Data Lake, A New Step Forward

In today’s world volume of data has been so large. This problem can be tackled through Hadoop-based Data Lake. A data lake is a storage repository that holds a vast amount of raw data in its native format until it is needed. There are some strengths, weakness, opportunity and treats.


A Hadoop-based data Lake is a low cost operation, as it is open source software and can be processed on low cost system. Hadoop has a capability of storing and processing all types of data, whether structured or unstructured, which incurs only a small proportion of cost of our currently traditional systems.


There can be a lot of confusion due to large volume, variety and velocity of big data. Although Hadoop-based Data Lake is open source and helped to meet the increasing demands of vendor’s products, it had not received complete success yet. There is a lot of security problem with this system. Open source community and vendors tried to eradicate such problem by supporting security and privacy requirement of the organization.


There is opportunity to find unknown data. In spite of the existing data agents can go through the data lake to have better answers, or they could even get the answers to the questions that were not able to find. Advanced analytics also changed the view. For example descriptive analytics provided better visuals of the situation. Advanced analytics like- prescriptive, predictive and diagnostic, helped to analyze big data. A Hadoop-based data lake provided such opportunity.


There is a significant cost and time involved to adopt these new technologies. It can affect the people, processes and the culture of the organization. Also there had been a lack of skills required to operate these advanced techniques which hangs on adoption of Hadoop. 


So, all we can conclude that with the presence of some weakness and threats there are some strengths and opportunities to explore. An organization can enjoy the benefits provided by data lake depending on its requirements. Read more at:

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