Use Typecasting

Transcript

In this video, we’ll guide you through how to use typecasting to adjust schema fields that were set incorrectly, enabling you to unlock powerful analytics capabilities. Let’s dive in. Typecasting allows you to temporarily adjust the data type of a schema field to make it usable for your analysis. For example, if a field like the number of search results was mistakenly captured as a string in your schema, you can convert it to a numeric field. Once converted, you can use this field in calculations, visualizations like histograms, or other numeric-based analyses, just as you would with any other numeric field. Another powerful use of typecasting is converting date or date-time fields into strings. This opens up opportunities to combine them with other data using additional derived field features, such as concatenation. For instance, on the screen, you’ll see an example of where we’re combining an entry page with the timestamp of when a user visited that page. This creates a new field that provides deeper insights into user behavior. Configuring typecasting is simple. Navigate to the derived fields section as shown here. Select the field you want to adjust, in this case a timestamp. Then choose the target data type, such as a string. You’ll have a variety of formatting options to customize the output. The system will apply the typecast based on your selection, making the field ready for further analysis. Thank you for watching this tutorial. I hope you enjoy experimenting with typecasting in derived fields to optimize your data analysis.