One of the really great strengths of Alteryx is that is can handle any amount of data that you throw at it. If your data is small enough, it might all be in memory, but when Alteryx gets more data than fits, it silently swaps out to disk. This way people are routinely processing data sets that are 2, 10 or even 100 times bigger than they have enough memory for!
Mostly the user never notices this aspect of the Alteryx engine and it just works. There are times though when we get feature requests that would be much easier to implement if all the data was in memory. One example of that is aggregate functions in the formula tool. Since other desktop products that are similarly easy to use, like Tableau and Excel, have simple SUM and AVG type functions in their formulas, it is assumed that Alteryx would too. Continue reading →
Update – there is an updated version of this macro in the post: Alteryx: Optimizing Modules for Speed.
There was a recent question on the Alteryx forum: How to use the percentile in summarize. The question misunderstands the percentile function in the summarize and is looking for something slightly different, although with similar math. So what does the percentile in the Summarize tool do? From the help:
Percentile: Calculates the specified percentile value for the group. The percentile is calculated by sorting the data and returning the row value relative to the specified percentile and its position in the sorted array – the largest value is the 100th percentile, lowest value is the 0 percentile, median is the 50th percentile, the 25th percentile is the value in the middle of the median and minimum, etc.
Continue reading →