This past week, DS 39 have been learning how to use Alteryx. Unlike the rest of my cohort, I struggled with picking up on how to use the software compared to Tableau Prep. This blog will review the fundamentals of Alteryx and simplify things for easier understanding.
Inputs and Outputs
Data from a local file or from a database can be connected using input tools. This can be done by dragging in a file or by setting up a connection. The input tool however, only displays a portion of the records in the dataset. To view the whole dataset within Alteryx, the browse tool can be used. The output tool is used to save the workflow to a file format of your choice. Remember to run the workflow, otherwise data will not be inputted or outputted.
Preparation Tools
These tools are mainly used for calculations and organizing the data. The four tools DS 39 have focused on this week are listed below along with their uses and examples.
- Filter - splits data into two outputs (True and False) based on a condition e.g. [Region] = 'South' produces two outputs of True (all transactions which occurred in the South region) and False (all transactions which occurred everywhere else)
- Formula - computes calculation ([January_Sales] + [February_Sales] produces a column of summed up Sales values, you can also update an existing column).
- Select - change data types, rename fields and select/deselect fields (rename [Sales] to [Yearly_Sales]
- Sort - change order of the fields (sort [Sales] in ascending order)
Join Tools
These tools are used to bring multiple datasets into one, the list below looks at the differences between Append, Join and Union along with their applications.
- Append Fields - attaches two datasets together from the columns, this should be used when no fields or records are similar in terms of data e.g. joining a dataset of addresses to a dataset of phone numbers
- Join - combines two datasets based on common fields (joining a dataset of sales and a dataset on store location through a store ID column)
- Union - similar to join but combines datasets based on common rows (dataset 1 contains patient data and dataset 2 contains genetic data and is combined through eye color record)
Transform Tools
Lastly, the transform tools, which can summarize and rearrange data. We will be focusing on the summarize tool which, can be used to compute summations, averages, maximum and minimum values. For example, summing the sales values to compute total sales.