The patterns in this chapter all have one thing in common: they don’t change the actual records. These patterns all find a subset of data, whether it be small, like a top-ten listing, or large, like the results of a deduplication. This differentiates filtering patterns from those in the previous chapter, which was all about summarizing and grouping data by similar fields to get a top-level view of the data. Filtering is more about understanding a smaller piece of your data, such as all records generated from a particular user, or the top ten most used verbs in a corpus of text. In short, filtering allows you to apply a microscope to your data. It can also be considered a form of search. If you are interested in finding all records that invo....