In this chapter, we used different techniques from Elasticsearch to gain insight about data modeling using real-world examples from IEX. We used the same examples to practice with different techniques. From the general recommendation, using data denormalization can provide easier management and maintenance and compose queries for search.
In the next chapter, we will introduce the aggregation framework. Aggregation can be thought of as a technique to build analytics on a set of documents. The framework consists of many building blocks that can be combined to build a complex summary of the data selected by the search query. There are many different types of aggregations, and we will cover the common methods, such as metric aggregation, bucket aggregation, pipeline aggregation, and matrix aggregation.