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SAS Advanced Analytics is good, but generally slow
January 19, 2019

SAS Advanced Analytics is good, but generally slow

Thomas Young | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with SAS Advanced Analytics

SAS Advanced Analytics is used only in certain departments that do advanced analytics. The program is used for data mining, text analyses, support vector machines modeling, ensemble modeling, neural network modeling, and various other processes. The program is part of an automation movement for processes that get repeated frequently, although most of the usefulness of the program is in the new modeling projects during the development process.
  • The user interface of SAS Advanced Analytics is one of the easiest I have used. The software is easy enough for a professional to self-learn. With that said, a professional should probably have some experience in advanced analytics to get the most use out of the software.
  • The web interface of SAS Advanced Analytics makes it easier to produce analyses from any computer anywhere in the world.
  • The number of options available for simulations is world-class. Additionally, SAS makes it easier than most other software tools to see exactly what it is doing. Other software tools built for the professional analyst are less straight-forward.
  • SAS Advanced Analytics takes a while to get doing. SAS could improve the startup process. Because the software starts so slowly, I have to be completely committed to doing analytics for a good period of time before I will open the software.
  • The default color schemes on Advanced Analytics are not very nice to look at. It's almost as if SAS read Tableau's playbook and said, "hey, let's do the complete opposite." Bad decision.
  • SAS could make the process of learning the analytics steps of SAS Advanced Analytics simpler. Although it is generally more simple than other tools, that doesn't mean it's perfect.
  • SAS Advanced Analytics is not the cheapest software on the market. The overall cost was weighed against free, open-source software tools. The overall return, I think, was quite positive because SAS Advanced Analytics saves enormous amounts of time compared to the open-source software tools.
  • At first, adopting SAS Advanced Analytics was a negative return because it took time for individuals to change their analytics habits and adjust to superior tools available at their discretion.
  • SAS Advanced Analytics has replaced the need to hire less expensive R or Python programmers. So, although the software requires an initial expensive upfront investment, the ease of use makes it so that other areas of expenditure save money.
SAS Advanced Analytics does a fairly decent job producing good results from user-chosen advanced algorithms. The software includes all of the most-often used advanced machine learning and artificial intelligence algorithms. With that said, although SAS Advanced Analytics has all the popular tools, and many of the less popular tools, the software is often not the first to release cutting-edge models. Other software tools, such as R or Python, typically beat SAS Advanced Analytics to the punch. With that said, for almost every applied, practical application, SAS Advanced Analytics is a much more useful product to put in place than the two aforementioned tools.
ArcGIS, Google Data Studio, Apache Spark, Tableau Public, Google Analytics, Google Analytics Premium, Apache Hive, Google Drive, Google Data Studio, Amazon Kinesis Analytics
SAS Advanced Analytics excels with projects that have at least 3 parts. The first part is the ability to address and compare different modeling types. Suppose you are an analyst interested in predicting home prices or whether an individual will reapply for unemployment insurance. There are lots of model types that could work for these two situations. SAS Advanced Analytics makes it easy (although not as easy as SAS Enterprise Miner) to compare the performance of different modeling types, such as comparing support vector machines with random forest models. A second scenario that SAS Advanced Analytics does a good job at is making the analysis reproducible. By showing the lineage of analyses, another analyst is able to follow the work of the previous analyst. This is a huge advantage for individuals working in corporations or governments. The third area SAS Advanced Analytics is useful is in text analytics. The field is huge now, and I haven't come across a software that makes text analytics as easy as SAS Advanced Analytics.