Just make sure you go back to the Input step to make those adjustments. Let Tableau Prep generate a default sample, then use the profile pane to see which fields or values you could remove. If you’re not sure what you can filter or remove during the Input step, the profile pane is a great place to identify those changes. If you have a large data set and want to use random sampling, you can reduce your wait time by making these changes together, or prior to changing the sampling method to random.
Tip: All changes made in the Input step will cause the data sample to be regenerated. By de-selecting the fields in the Input step, the data is never loaded into Tableau Prep, which improves performance and allows for a larger sample size. If I bring in flight data (used in the screenshots above), there are several fields that are mostly nulls, which I know I’m not going to use in my analysis. But if I filter the data at the Input step, the filter will be applied first, and I will get 150k records coming from 2015 into my sample. If I filter these records from the cleaning step, 100K rows will be removed after the data is sampled, leaving me with only 50K records from 2015. In the example below, I notice that my file has unwanted records from the year 2014. If you are filtering data to limit the values in a certain field, applying the filter in the Input step will improve performance and help you get more out of your sample. You want to generate a larger sample or use all of the data (there may be too many irregularities to clean the data effectively with a small sample).You want to generate an even smaller sample (you know the data well and want to streamline the prep experience as much as possible).This is common when you have data that is ordered by date, or if you are using a wildcard union. the default settings only pulled data from 2005 when the data set covers 2005-2018). You need a more representative sample (i.e.Text-heavy data sets will therefore return a smaller number of rows when sampled than data sets that are predominantly numerical.Īlthough Tableau Prep has helpful defaults for sampling, you may find that you need to adjust the sample, for reasons like: Fields with a string data type are usually larger than a numerical data type. This means if you have 300 fields, you'll get fewer rows in your sample than if you had 5 fields. Data sets with more fields will result in a sample with fewer records (rows) than data sets with fewer fields. In most cases, data over one million rows will likely be sampled the default sample amount is based on the number of fields, and the data types of the fields, not number of records. Reference Materials Toggle sub-navigation.Teams and Organizations Toggle sub-navigation.Plans and Pricing Toggle sub-navigation.
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