MongoDB is a high performance, open-source document-based database. Data in MongoDB is stored in JSON-like documents with dynamic schemas, providing flexibility during the development process. MongoDB has built in support for horizontal scalability with solutions for redundancy and failover as well as support for easily scaling reads and writes.
That's all well and good but what do you do with your data once it's in MongoDB? Your app is successful and you're capturing lots of interesting information but how do you make sense of it all?
In this session we'll talk about different strategies and approaches for analyzing your data in MongoDB. We'll walk through the aggregation framework and show how you can pivot, aggregate and explore your data with some live examples. Next we'll talk about where MongoDB's native MapReduce mechanism can be useful for advanced tasks. We'll also discuss data storage approaches for pre-aggregation to make data roll ups easier to generate.