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Big Data Solutions


Traditional Enterprise Approach

Under this approach an enterprise will use a computer to store and process big data. For storage purpose, help will be availed of their choice of database vendors such as Oracle, IBM, etc. In this approach, the user interacts with the application, which executes data storage and analysis.





This approach ideal for those applications which require low storage, processing and database capabilities, but when it comes to dealing with huge amounts of scalable data, it imposes a bottleneck.



Google solved this problem using an algorithm called MapReduce. This algorithm divides the task into small parts and assigns them to multiple computers, and intermediate results together integrated results in the desired results. Intellipaat’s Big Data Hadoop training will help you get a better understanding of Big Data Solutions in Open Data Platform!





Google’s Doug Cutting and his team developed an Open Source Project known as HADOOP to handle the large amount of data. Hadoop runs applications using the MapReduce where the data is processed in parallel and accomplish the entire statistical analysis on large amount of data.



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