Wir helfen Unternehmen seit 17 Jahren,
bessere Software zu finden
SAS-STAT Software
Was ist SAS-STAT Software?
Statistisches Analysesystem, das Unternehmen eine breite Palette an statistischer Software zur Verfügung stellt, die von der traditionellen Varianzanalyse bis hin zu exakten Methoden und dynamischen Datenvisualisierungstechniken reicht.
Wer verwendet SAS-STAT Software?
Nicht vom Anbieter bereitgestellt
Du bist nicht sicher, ob SAS-STAT Software das Richtige ist?
Mit einer beliebten Alternative vergleichen
SAS-STAT Software
Bewertungen über SAS-STAT Software
SAS- the best analytical tool.
Kommentare: By using SAS one can easily transform data in better format to interpret some result and make decision. SAS is very good tool for data transformation.
Vorteile:
SAS is developed by SAS institute which is useful for analytics like statistical analysis, predictive analysis, business intelligence. It is a very good tool for data processing in which data stored, processed and analysed to make it useful for analysis. It is done in linear and tabular forms which is useful for better data understanding. It is useful for decision making and to make data easily understandable by others.
Nachteile:
It is quite difficult to understand functionalities of SAS. It can be accessed by professional who knows how to handle software.
SAS Review
Kommentare: Good. I feel like a learn something new everyday especially when handling data request. Doing the SAS training for certification were also incredibly helpful in expanding my understanding of what all I could do in SAS.
Vorteile:
1) That the rules are relatively consistent making it easier to learn more and more technical jobs once you've got the basics 2) SAS will make you check you work and has useful error messages and alerts 3)that shear scope of procedures and step options available for data analysis. It offers users numerous back up options if they are not sure how to get one particular procedure to work
Nachteile:
1) There is a definite learning curve with SAS and it takes time and patience to practice at it. It's worth it but other systems are slightly more intuitive. 2) SAS is not the best when it comes to data visualization tools like bar charts.
As a user of many open source alternatives, this felt like a step backwards in many regards.
Vorteile:
It is reliable and a can handle medium-large datasets without breaking a sweat. The flow of the SAS scripts is usually straightforward and readable for basic data manipulations. It allows SQL to be embedded which is what I take advantage of in 90% if the code that I write. The documentation online is throrough across the board, especially compared to the scattered nature of documentation for R or Python.
Nachteile:
Rigid structure of the code and requires a lot of bad practices such as copying and pasting code blocks. This leads to thousands of lines being necessary when I could write only hundreds in another language. There may be more efficiencies I could take advantage of, but as an intermediate user I do not have time to learn the intricacies of this tool that is so different than everything else out there. Also, the high price is causing my organization to shift away from this software, but the pricing structure makes it hard to lower our usage without scrapping it all together.
Easy to use and all-in-one analytics software
Kommentare: I am developing statistical models for financial industry using SAS. In addition, I am doing portfolio analyses and also model monitoring tasks within the tool
Vorteile:
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
Nachteile:
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 is the gold standard software for pharmacutical industries
Kommentare: SAS is great and has great documentation and SAS also provides a lot of great books. I have not no problem with its difficulties because I know every good thing has costs.
Vorteile:
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.
Nachteile:
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.
The original power statistical tool
Kommentare: Use it just for the sheer power. Quite expensive licenses and there are certainly better and faster packages available. Its just that migrating system from a foolproof and proven system just seems too much of work. Hope they up their game plan soon or soon, it might be time to make the plunge.
Vorteile:
Very powerful. You want it and you can do it. Quite intuitive programming. Has multiple ways to integrate with other packages for data exchange. Has a reasonably versatile scalablity.
Nachteile:
Its aged. Much slower than some of the latest products in the market. Syntax while not complex can hardly be described intuitive Interface seems at least a couple of decades old.
SAS is my program of choice for most of my methodological research.
Vorteile:
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.
Nachteile:
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.
Good variety of analytics tools
Kommentare: Used SAS to do a bunch of design processes and quick analysis on a large relational database. I did get certified in SAS, but even I will admit that I still hardly feel comfortable coding on my own, so I still rely on the GUIs.
Vorteile:
There are a lot of different SAS softwares to fill a variety of uses. If you have a problem, then SAS has almost certainly already thought of it. Some of their GUIs are very user-friendly too.
Nachteile:
Learning how to code in SAS is a real pain if you've ever learned any other coding language. It's just way different than anything else.
Good support and very good at what it does but archaic and not as easy to use as some alternatives
Kommentare: Well tested software that can do a lot of statistical analysis quite fast.
Vorteile:
If what you want to do is supported in a proc then it can be very easy to to get your work done. The documentation is *very* good.
Nachteile:
If what you want isn't supported you *might* be able to find a macro online. But the macro language is very archaic feeling especially compared to R or Python. The graphics used to be terrible but they have gotten quite a bit better over the years. It's also incredibly expensive especially when you compare it to R (free and open source).
SAS is powerful, but complex
Vorteile:
SAS is extremely powerful and able to handle very large datasets. Management of tables and databases are relatively easy to manage and ensure that not all users rewrite tables.
Nachteile:
The coding for this program is by far the least intuitive language I have learned. That being said, once you understand the basics with a large learning curve, it's not that hard to do pretty much anything you want to do.
Complete Business Intelligence Suite
Vorteile:
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.
Nachteile:
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.
SAS for Analytics
Vorteile:
There are tons of examples and answered questions available with a simple Google search. You can generally figure out how to accomplish your task by doing a little research.
Nachteile:
The interface could use some updating...it seems old and dated. Need to intriduce new functionality in order to keep up with R and Python, which I prefer using.
Sas the best software for Research data analysis
Kommentare: Overally im impressed with SAS.
Vorteile:
The software is a wholesome package for data analysis as it gives not only the anovas but also the graphical output which is very ideal when making presentations and when presenting your findings be it in a thesis or for business. Its easy to use since you just need the code to run your specific analysis and you are good to go. It saves you a lot of time in that it works nicely with outputs from other statistical packages when you want to do advanced analysis, there is no or minimal manipulation when you want to run such output using SAS.
Nachteile:
The fact that it is not a free software, one that you can use without a licence
SAS is the benchmark software in the field I work in (biostatistics)
Vorteile:
It is the most validated software in the analysis of data from clinical trials and Bioequivalence. The standard accepted by the regulatory authorities.
Nachteile:
Somewhat difficult to master. But the huge documentations availability resolve any faced issues
Love the idea of SAS, but too complicated
Vorteile:
I love that SAS allows highly complex and conservative analyses so I know that my findings are valid and fair; I am always confident that my results can generalize to others because SAS allows more analyses.
Nachteile:
It really requires a statistician or engineer to be able to use all of its tools, and I am neither, so I rely on SPSS.
my favorite statistical analysis app
Vorteile:
SAS/STAT is my favorite statistical analysis app. Its plenty of fully tested PROC packages provides excellent ways to fulfil my analytical tasks.
Nachteile:
Dealing with big size data is a problem.
Expensive and heavy software
Vorteile:
can handle large scale data very easily. Industrial scale software to run big data
Nachteile:
installation takes a long time and consumes a lot of space on your PC. Doing the same thing in Python takes less effort.
Good for data work at low level
Vorteile:
Not a very steep learning curve, plenty of resources online for help with code
Nachteile:
Few data presentation options, model options, non-intuitive syntax
An astoundingly Powerful tool that allows for quick and effective analysis and a whole heap of stuf
Vorteile:
Quick and seamless integration with Microsoft office based tools. Easy manipulation of data in terms of reporting
Nachteile:
Can be quite challenging to get your head around the different uses for the software just the massive scale can make the software overwhelming
Great paid software for statistical analysis
Vorteile:
The software is a paid one and thus it has a wide amount of tools and support for use, it also has an integration with other tools such as JMP Genomics.
Nachteile:
The software is aimed mainly at analysis but does not allow you to go for the full extent of developing new techniques for analysis as you can with open programming languages such as R.
The start up tutorial was helpful for those starting from scratch.
Vorteile:
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.
Nachteile:
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.
very good software, takes time to pick up
Vorteile:
Can do just about any analytics operation one might need quickly. Documentation ins extensive and helpful.
Nachteile:
The UI is difficult to get used to. Graphs and other visualizations aren't as good as other competitors.
Grad school
Vorteile:
Used it for most research, including dissertation. Easy to learn, not too complicated with coding.
Nachteile:
It’s a bit of a headache to learn all the macros and such.
SAS has allowed me to perform functions that used to take hours to do within a matter of minutes.
Vorteile:
SAS takes a bit of time to get comfortable with, but once I gained a base level of competency with the program, I found that each new function was easier to understand / utilize.
Nachteile:
The SAS coding language is not user-friendly; other statistical programs have more easy-to-understand and intuitive coding language, but lack the functionality and breadth of programming capabilities that SAS has.
Great program for what I need to do!
Vorteile:
I like that the software is very versatile that has lots of features and able to run many scripts to extract Data.
Nachteile:
It is a very difficult program to run. It is not for the amateur computer person. It requires high level skills.