SAS-STAT Software Reviews

I love the output style and how the software is insured to produce the best possible output. Additionally, I like the log feature which helps you debug your code. I also like that the syntax is mostly not case sensitive (with the exception of literal strings).

There is a learning curve to this software regarding the language. But, there are free and affordable modules on the website and at you local library that you can check out to learn how to program in SAS. The software is expensive as well, but for what you get it is work the money.

can handle large scale data very easily. Industrial scale software to run big data

installation takes a long time and consumes a lot of space on your PC.

Doing the same thing in Python takes less effort.

SAS Enterprise Guide is the tool a data scientist will be able to perform all data preparation and analysis tasks with both hard coding or drag and drop functionalities. Even some forms of models can easily be developed within the tool. On the other hand, SAS Miner is also very useful for statistical model build. The advantage of all these SAS tools is the visibility of the data from all these tools as they are integrated with each other

As data science word is evolving in a very fast pace, SAS should also align itself to this world. SAS sometimes stays behind the popular algorithms which could be done with R and Python. I am sure they will also be covered soon within the tools.

SAS-STAT provides a lot of statistical procedures but from the point of view of an experienced Statistician, this is not the main advantage of SAS with respect to its comparators including R and Stata. SAS is recognized as the gold standard statistical software for biostatistics and statistical programmer job titles in the pharmaceutical industry where the cost of software is not important with respect to the overall cost of drug development. So the main advantage of SAS is its prestige that facilitates some of the challenges in submitting drug development applications to governmental agencies.

Working with SAS is not easy for most statistics graduates where they are well familiar with R. On the other hand, Stata software is also complete and is menu-driven so it is easy to use. Hence, the only reason that you may need to chose SAS is just its prestige.

SAS 9.3 gives you tremendous power to clean, manipulate, and analyze large datasets. I've been a SAS user for a while and prior to that I had only worked with SPSS. SAS opened the door for me to think about my data differently. I've used SAS now on criminal sentencing data, healthcare claims data, and operational case management data. Whether you need to create an automated report, write algorithms to mine data, or prep a dataset for another software like Tableau, SAS is a fantstic tool. Additionally, SAS has a litany of trainings available for purchase to help you get the most of your data.

SAS is very costly. It's important to keep in mind that in addition to being a product, SAS is also a programming language that as of writing is not patented. If you are on a budget there is a company out of the UK that sells a software that runs Base SAS programming language for a fraction of a price, great for outfitting a startup team. SAS Graph module leaves something to be desired, there are better softwares that focus on just visualization.

What I love about SAS are syntax consistency and standardized functions. SAS as an institute has been doing a great job at maintaining the software and providing great experiences to its users. Whenever I face an error, the message often tells me what to fix exactly whereas other programming languages like R doesn't - it's extremely annoying and time-consuming.

One thing SAS lacks - perhaps it's just because of the nature of the software - is its visualization capability. I'd do a lot of statistical analysis in SAS, but have to find an alternative way to create figures to convey the results as the graphics look like they're from 90s.

The functionality and ease of SAS is unparalleled for conducting a variety of advanced analyses, especially in GLM and multilevel (HLM) frameworks. I find when writing code for the same analyses with the free software R that for more complex analyses, the R code is always much longer. Additionally, SAS documentation is very thorough and it is always easy to find the answers you are looking for.

The graphics. SAS graphics are so basic and look so dated that I often use a different program to generate plots, even though they are easier to generate in SAS. The graphics really need to be updated. Also, the SAS capability for structural equation models (SEMs) is limited, and I usually use Mplus for those analyses.

I use the software to accomplish 80% of my duties so I may be a bit biased.

The software is extremely flexible allowing you solve many problems using its predefined processes and functions. It can be used to solve many types of reporting problems. It has built in solutions to many common and uncommon statistical and business problems.

It has a variety of interfaces that are available to clients, depending on what a user needs they might choose to use different tools that are available to them. The whole suite is actually quite large and most users will only ever touch the parts of it that helps them accomplish their goals. The SAS eco-system is extensive, mature and well-developed. We rely on it for many mission critical solutions.

Often times the various prebuilt processes have their own syntax and they are not consistent throughout the application. The software package is not cheap.

SAS-STAT offers industry best statistical interferences, reports and all other items can be generated using regulatory guidelines.

No pre-built report templates, UI is pretty old, still has to write code for reports.

I am using SAS since last 8 years and I have used it in DWH using DI studio, SAS EG for reporting and Web Report Studio, SMC etc. I can say it is the best solution of all problems related to data and works perfect. You need to have expertise to work around this but it is not that tough to learn like Java etc.

Cost effective and you need to have technical expertise to work around this tool. some functionality are tough to learn and it may take years to be expert on this tool set.

It gives us more easily accessible tools to manage data, clean, subset, merge and combine to prepare for analysis and further to analyze datasets.

The cost of the software is high and increasing to the level that sometimes hard to renew every year, to cope up with other incremental expenses of life.

easy to analyze statistical data, I tried from R, and then I used this one, it is quite impressive for statistical analysis.

there is nothing least, but we need to arrange the data in chronological order so that the software pulls up the data very easily without having any hurdles.

I love that it has all the components to run and collect data

I don't like that the user interface looks outdated.

SAS has the excellent ability to handle large database sets, and the syntaxes required for the software is also easy to learn. and to conclude, I love the fact that every algorithm in SAS are tested before implementation so adequate results can be arrived at.

I don't like the fact that it has very less graphical representation capabilities. There are better software wherein much more detailed graphical plots and diagrams could be plotted.
And last but not least, SAS is very expensive software to operate and licenses are needed to operate in comparison to other open source software.

I like the great feautures of creating and using the libraries for your custom code and forecating model is very easy to create.

The interface is still using old legacy system and I believe need to upgrade the interface ,so it is rich and light.

Analysis functionality is very good to do all different data analysis, like modeling, prediction, or basic function.

Visualization can be improved, like all the charts. Because of price, usually used in big companies.

Coding allows for personalized data analysis and ease of use

Can be difficult to troubleshoot issues as helpmmenus are unclear and frequently link to pages that are not related to core issue

It's powerful, useful for large datasets, and lots of options for analyses and visualization.

Cloud-based version took some time to figure out. Documentation support would help users during the transition.

It allows me to display my data in a more powerful way and there are guides on SAS.com to walk you through more in-depth processes.

It looks like it was made in 1995. I also had issues with SAS 9.4 being 64-bit. I had to change my code so it would run because of this.

Used it for most research, including dissertation. Easy to learn, not too complicated with coding.

It’s a bit of a headache to learn all the macros and such.

Easy in the eye looks for coding. Intuitive error finding when writing code by colors contrast. Runs relatively fast.

Can be a bit overwhelming if you are not used to coding. Sometimes will run the solution and the results will not make sense without any warning from the software. Depends on service availability.