As mentioned in the introduction to this chapter, it is generally considered good practice to transform your data, including merging from multiple sources, before it arrives in your analysis tool. However, you might not have this facility or access to good data integration tools, or perhaps you just want to explore something quickly to follow an analytical hunch. Spotfire provides some easy-to-use and powerful data transformation tools.
In brief, here is an overview of some different data transformation methods and a short explanation of when you would use each of them:
- Data wrangling in Spotfire: This is great for ad hoc data analysis–load data into Spotfire, transform it, filter it, add calculations, and so on. You can also use data wrangling to design a data workflow for implementation in another tool later on.
- Data virtualization...