Combining datasets using an inner join
We often store in multiple different places for a variety of reasons, including different systems, storage optimization and efficiency, security, costs, and so forth. When analyzing data, however, we often want to bring data from many different areas together to create a richer dataset for analysis. Doing so may result in a better understanding of the data and provide valuable business insights. We can use the Join functionality to combine data horizontally, that is, widen the dataset by adding fields from two or more sources together. There are a variety of different join types, as you can see by the recipes in this chapter. In this recipe, we'll look at creating an inner join.
An inner join is the end result of joining two data sources together and retaining only those rows that overlap. For example, let's assume we have order data for a B2B seller of office supplies. Their data may be segmented into a database containing order...
