My advice — even if others aren’t hitting it, it could be due to differences in default string lengths or client-side SAS settings. Try explicitly setting the length for my_column in your proc sql query, e.g., select cast(my_column as varchar(1000)) as my_column ... View more

From my perspective, the coolest part is how it combines data from multiple sources—transaction history, location, device info—and gives you actionable insights. I’d personally focus on setting up clear rules for high-risk transactions, but let the system adapt over time for borderline cases. That way, you’re not manually chasing every weird transaction, but you’re still protected. ... View more

why? ... View more

If it were me, I’d probably lean toward keeping the variables consistent across all years, even if it means creating some dummy variables for the older datasets. It makes analysis way smoother later on, especially if you’re comparing trends over time. You can always document the differences in your data dictionary, but having a unified set of variables saves headaches when running models or aggregating results. ... View more

these updates sound pretty solid makes the whole credit loss thing feel less like wrestling spreadsheets. Smarter adjustments and scenario stuff actually being “intuitive” is a win, because let’s be real, most of us just want to get insights without banging our heads. Curious to see if the attribution tweaks really make it easier to see what’s driving changes if that works, could save a ton of time. Overall, seems like SAS is finally listening to people who actually use the platform, not just adding buttons for the sake of it. ... View more

Handy feature cool that it tracks both UI and API actions. Makes it way easier to keep tabs on who did what without digging through logs. ... View more

I’d go with dice, simple and super clear, you can show probabilities and distributions right away. Cards are fine too, but dice give that quick “wow effect” for teaching. ... View more