In many of our use cases, the data we work with does not come ready to be fed into an analytics workflow. It must first be ingested and prepared. This includes renaming and/or reordering fields, changing data types, filtering out invalid values, and combining different parts of the same data source. In this post, we will be covering how to perform these steps using a Data Pipeline tool called Alteryx. We will walk through a workflow used for one of our clients.