We use SAS Enterprise Guide in my org it has a visual SQL generator similar to what is previewed it is quite good for simple queries but I find it falls down wh

We use SAS Enterprise Guide in my org it has a visual SQL generator similar to what is previewed it is quite good for simple queries but I find it falls down when you introduce complexities. Joins between tables are one of the big pain points for me. I am not sure how the demoed product does joins but in SAS EG you join tables by click and dragging a line between the two columns you want to join together and then it gives you a pop up to select Inner, Outer, Left, Right etc. (although it uses plain English. I.e rather than saying "left join" it says something like "All Rows from Table 1 and matching Rows from Table 2) it also gives you a visual Venn diagram type preview. This is frustrating for a few reasons: if table is large i.e several hundred columns you have to scroll for an eternity to find the columns you want to join against which is frustrating (a drop down box you can use keyboard shortcuts to jump to column name would be much better UI IMO). It is difficult to do complex joins "Where A.Col1 Between B.Col1 and B.Col2" for example. Maybe just my org but this is common feature of our data we have a lot of Event driven stuff with Start and End date and then Raw time series data you need to aggregate between the event frames. SAS's Timeseries stuff is very good but SQL side not so much... It is also very easy for unsuspecting users to join on unindexed columns which leads to very poor database performance. In general there are a lot of performance footguns with generated SQL user can have working query then change something in the GUI and suddenly query that ran in subsecond takes several minutes. I have developed the habit that for complex I use GUI to generate SQL then hand edit it before running it to make sure it will be performant. Or I just hand write it to begin with. Pattern matching and filtering is another pain point the query editor lets you use "LIKE" but does a poor job explaining to user how it works people who only use the GUI are surprised when I explain you use "%" and "_" to do character expansion a lot of people blindly assume "*" is used and then complain their query isn't working Microsoft Power BI also has a query editor I've used this program a little bit but do not have as much experience from what I experienced using it I found it to be a bit less flexible it seemed easier to do the data extract and transformation first then load it into Power BI.