Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Data aggregation is one of the key features used in databases, especially for Business Intelligence (e.g., ETL, OLAP) and analytics/data mining. When considering SQL databases, aggregation is used to prepare and visualize data for deeper analyses. Hover, these operations are often impossible on very large volumes of data regarding memory-and-time-consumption. ,  show how NoSQL databases such as MongoDB and its key-value stores, thanks to the native MapReduce algorithm, can provide an efficient framework to aggregate large volumes of data.  provide basic material about the MapReduce algorithm, the different NoSQL databases (read intensive vs. write intensive).  investigate how to efficiently modelize the data framework for BI and analytics. For this purpose,  focus on read intensive NoSQL databases using MongoDB and  show how NoSQL and MapReduce can help handling large volumes of data.
['Laurent Bonnet', 'Anne Laurent', 'Michel Sala', 'Bénédicte Laurent', 'Nicolas Sicard']
I am writing a research paper on a idea Reduce, You Say: What NoSQL Can Do for Data Aggregation and BI in Large Repositories
[{"from": "human", "value": "I am writing a research paper on a idea Reduce, You Say: What NoSQL Can Do for Data Aggregation and BI in Large Repositories"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Data aggregation is one of the key features used in databases, especially for Business Intelligence (e.g., ETL, OLAP) and analytics/data mining. When considering SQL databases, aggregation is used to prepare and visualize data for deeper analyses. Hover, these operations are often impossible on very large volumes of data regarding memory-and-time-consumption. ,  show how NoSQL databases such as MongoDB and its key-value stores, thanks to the native MapReduce algorithm, can provide an efficient framework to aggregate large volumes of data.  provide basic material about the MapReduce algorithm, the different NoSQL databases (read intensive vs. write intensive).  investigate how to efficiently modelize the data framework for BI and analytics. For this purpose,  focus on read intensive NoSQL databases using MongoDB and  show how NoSQL and MapReduce can help handling large volumes of data."}]