An online business increases conversion efficiency by quickly processing and analyzing huge amount of data generated by its network
The company manages an online network and has one of the largest audiences in its business vertical. They provide services over their network to various businesses and enable them to connect to their audiences.
Big Data Management Services, Cloud Computing
HDFS, MapReduce, MySQL, Java/.Net
The business could immediately improve conversion because they now have access to the additional features from the data. Operational changes to the network could be better managed and monitored.
This solution expedited many other processes which were dependent on this data. Better features could be provided to the business owners on various dependent systems. The cost of procuring and maintaining high-end systems was reduced considerably with the use of on-demand cloud computing. Since most of the technologies used in the solution were open source, any additional software expenses were eliminated.
The large set of audience produced a huge amount of data on the network. This data featured a lot of valuable information which should be used for business intelligence. Primary purpose of this information was to improve conversion and expedite operations.
The data produced and used daily by the network is from multiple sources and it is big. So Big that conventional databases cannot turnaround the processed information within an acceptable time frame unless some very powerful systems are used. Also, in their current systems, significant information could not be used due to lack of processing abilities. The company needed a solution where this data can be processed and consumed within an acceptable time frame and is not too expensive.
After reviewing the problem, Continuity1 provided a data management solution which would manage the data and could also scale in future. The solution was to persist entire data on adistributed file system and then processit using distributed computing techniques. An on-demand cloud computing infrastructure was employedand MapReducewas used to process the data and extract features. Distributed computing combined with the principles of data warehousing provided a very time efficient way of processing data without any loss of features. Thus, making the right information ready for the systems who need to consume it.