SAS Studio

“Liked the browser-based access with no install and good handling of large databases. Found that storing data on vendor servers adds significant cost.”

“Liked the big data handling, online collaboration, and machine learning support. Found that it requires a stable internet connection, which makes travel use difficult.”

“Liked the reusable macros, large dataset handling, and strong community around the language. Found graph procedures such as PROC SGPLOT hard to use and customize.”

“Liked the ease of use, quick learning curve, reusable macros, and speed on big data. Found the license cost high and importing or exporting through local folders slow.”

“Liked covering the full model lifecycle, a common language across products, and background jobs. Found no offline access, no auto-save, and no progress alerts for background jobs.”

“Liked how easy it is for people already familiar with SAS Base. Found Git integration poor and data visualization options lacking.”

“Liked the stability and speed on large data, macros, easy account setup, and many input formats. Found uploading large data to the servers slow and in need of planning.”

“Liked the speed regardless of local hardware, wide statistical procedures, and time-series tools. Found building folder structures slow and big data code optimization demanding.”

“Liked the intuitive interface with autocomplete, broad analytics including machine learning, and remote access. Found the layout rigid and connecting external data sources complex.”

“Liked the large data handling, suitability for junior and senior analysts, and wide documentation. Found it weak for custom reports, so results often go to Excel.”

“Liked the stability with large data volumes, the flexible and simple language, and multiple input formats. Found license and online storage costs high.”

“Liked the user-friendly design, flexible code, device access, backtesting, and responsive service. Found that files must be downloaded one at a time with no bulk option.”

“Liked the speed on large volumes, minimalist interface, macros, SQL support, and customizable charts. Found it creates ecosystem lock-in and customer service slow though accurate.”

“Liked the intuitive language, strong models, and quick productivity for junior analysts working remotely. Found it expensive, dependent on a good connection, and unavailable during server outages.”

“Liked the flexible cloud setup, fast processing of large datasets, and many regression procedures. Found that all data and code must sit on the server, blocking third-party search tools.”

“Liked the very fast computation on big data and simple browser-based rollout. Found moving files to a local computer cumbersome and reliant on workarounds.”