Reviews (1-13 of 13)
January 18, 2020
We piloted SAS AA at my organization to see how well it compares with other free software tools such as RStudio and Anaconda. So far what we saw was very impressive especially with the visual display but was a little out of our price range. Nonetheless, we were very impressed with the tool overall and would recommend it to other companies particularly those with limited programming expertise.
Read Yoni Dvorkis's full review
We piloted SAS AA at my organization to see how well it compares with other free software tools such as RStudio and Anaconda. So far what we saw was very impressive especially with the visual display but was a little out of our price range. It would be useful in analyzing population health metrics combined with financial data.
Currently, we are using it for a strategy engine that makes decisions on accounts and members' credit accountability and sends the decision to other collection systems. Various analytical and predictive models are built using SAS Advanced Analytics.
- Well established predictive and statistical models
- Easy to code using base SAS as it supports multiple analytical procedures and functions
- Easy to execute and maintain
- Enhanced reporting capabilities
- Better visualization
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Mostly suited for OLAP systems where analytics is performed on data, not for OLTP systems.
January 19, 2019
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.
Read Thomas Young's full review
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.
May 22, 2018
Score 7 out of 10
Currently, in our organization, SAS is used for highly statistical analysis of customer engagement data. We also use for forecasting the customer engagement pattern with SAS. In this capacity, we use a special tool called Forecasting Studio for Desktop as well which has built-in models available for statistical and events based forecasting.
- SAS is can be used as query builder tool which can automate a lot of excel process.
- There are variety of statistical options available that tie up good visual analytics.
- There are inbuilt models available for different operations which doesn't require any coding and are easy to run.
- Query builders have less functionality compared to some tools like alteryx.
- Modifying and customizing outputs are still a cumbersome process.
- Coding for special tasks is difficult and lengthy.
Read Rishi Bavishi, CSSGB, CAPM's full review
SAS is useful where you have special coding skills available on a team for this language and thus makes it a very useful tool in visual analytics as well as forecasting and data mining. While the software costs are really high, there are tools that are open source which can be useful for medium level tasks.
Was used by two departments to solve all analytical requirements. The software was used primarily to address data quality, summary analytics, predictive modelling, and insurance rate setting needs.
- Extremely versatile combination of available functions
- Includes all critical analytical capabilities
- Includes and interface to R for the few, newer approaches, that haven't yet been incorporated
- No needed improvements. Company continues to add more capabilities each year
Read Arthur Tabachneck's full review
Well suited for virtually any and all analytical needs for both large and small data needs. Combined with other SAS capabilities (e.g., data cleaning, manipulation and summary, graphics, visual analytics, data mining, and text mining, I have always found it well suited to provide the best solution for all analytical needs
November 18, 2016
It is being used for data visualization with quick and highly responsive dashboards.
- Good data preparation tools
- Well written code with few critical errors
- Responsive customer support
- More focus on presentation aspects with additional graph objects like donut pie charts
- More focus on production readiness including high availability and automatic monitoring of logs
Read Sanjeev Pulapaka's full review
Excellent for analytics of massive amounts of data and highly responsive dashboards. Less suited for traditional table like BI reporting.
My organization uses SAS Analytics for advanced analytics. It is used in various departments, including human capital and information management. It is used for predictive modeling, data manipulation, clustering and optimization.
- SAS Analytics is excellent for modeling. You can use a variety of modeling techniques and SAS Analytics produces robust reports on the model you are creating.
- SAS Analytics is excellent for data exploration. It has good etl capabilities, and once you have the data loaded you can preform a lot of statistics and other explorative measures.
- SAS Analytics does not have very good graphic capabilities. Their advanced graphics packages are expensive, and still not very appealing or intuitive to customize.
- SAS Analytics is not as up-to-date when it comes to advanced analytical techniques as R or other open-source analytics packages.
Read Remy Welch's full review
SAS Analytics is best for preforming advanced analytics for personal exploration.
December 04, 2014
We utilize SAS first and foremost to construct and implement multiple predictive models across our business units. Not only does it allow for quick and easy model construction, but the time it takes to cleanse the data between large or small datasets is relatively similar so dataset size is not an issue. In addition, we are also in the early stages of using SAS and SAS Office Analytics to create an intelligent reporting platform via Microsoft Office products and the SAS Web Portal. This allows our organization to traffic important data and information to non-SAS users through automated processes. SAS also has impeccable format style making the final drafts look very nice and easy to understand. SAS Enterprise Guide is our point and click interface that allows power users to access the full potential of SAS without needing to know coding off hand, but can also choose to do so if need be. We can also access any datasource using the ODBC connection that comes with SAS Office Analytics so accessing the data from any server or database is not an issue at all.
- Predictive Analytics
- Business Intelligence
- Report Automation
- Statistical Analysis
- Expanded point and click options under the data tab.
- Better resource information to help with circumstantial issues (i.e. graphing).
Read Nathan Och's full review
Key questions would center around what the user wants to do with SAS. For instance, before asking about SAS capabilities a user must be able to make sure SAS is compatible with their database setup or schema. After assessing the compatibility the user should ask if SAS has the ability to transform or manipulate the necessary data to get it into presentable form. It is really important that SAS demonstrates that it can add value to your data. Finally, after concluding that SAS is the right fit for how an organization wants to represent their data it is vital that the end user understand the limitations with SAS in regards to how their final product can be represented. Because SAS has many different modules and software a company can purchase the end user must find the most compatible package. For instance, if presenting data in Excel is a high priority the end user must be required to have the SAS MS Office Add-in that allows direct access to all of Microsoft's Office products. WIthout this, the end user may be limited in how they will be able to present information.
November 11, 2014
Score 2 out of 10
My team used SAS to integrate data from across our organization into an End Customer marketing and sales database for use in reporting and analysis.
Read Bethany Klebanov's full review
While SAS is great at what it does, the price is too high. The high cost issue is even worse if you want to do anything outside of the basic package. It's extra to link directly into databases, it's extra to get the module that allows you to do time series, etc. We were even charged a huge fee because we had one resource who lived in Canada. He was accessing the same US based server as everyone else on the team, the charge was solely because he was outside the US. Given the other options that are out there, it's increasingly difficult to justify such a high price point and antiquated pricing model.
September 12, 2017
I currently use SAS Advanced Analytics to analyze data coming in from the state level Behavioral Health Risk Factor Surveillance System and the Youth Risk Behavior Survey. I focus on tobacco data and SAS is extremely important when looking at this data. I use SAS STAT to analyse the data using survey procedures. Because BRFSS and YRBS are complex surveys I must use the survey procedures in SAS to get weighted frequencies, means and estimates. It is extremely easy to use SAS for these analyses, because the procedures are pretty repetitive. However, I do wish that the strata, weight, and cluster variables did not have to be typed with each procedure done. When using STATA or SPSS these variables are entered once, and the weighted results are automatically given when writing procedure. No need to enter them in for each. However, I am more comfortable with SAS coding and really like that it is user friendly. The online support for SAS is wonderful as well.
- Complex Survey Analysis- SAS is a great resource if you need to analyze complex survey data. One can easily write code for this by inserting (survey) in front of the procedure with the weight, cluster, and strata variables. (ex: surveyfreq)
- Modeling/ Graphing- SAS creates clean and easy to understand graphs and models which take visual data to the next level.
- Support- There is a large SAS Advanced analytics online support in place. It is easy to find help on many procedures that you will use in this software.
- SAS requires a lot of coding compared to other software like STATA or SPSS. However most of the code is repetitive , an easy copy/paste.
- SAS Advanced Analytics is not always easily learned, most people would need some training before getting comfortable with the software.
- The layout of the modeling system may get confusing when too many different windows are open, may need to look at different graphs and models one at a time.
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SAS Advance Analytics is well suited for data that is visual. Data where you want to see multiple graphs and models are good for this software. However, if your data is more descriptive this may not be the best program. SAS is well suited for data where you need to make comparisons on the feasibility of two different programs. Data that can be compared is perfect for this software.
SAS Analytics is being used by the marketing department in the organization. It is used for building a predictive model which eventually increases the return on investment on marketing campaigns.
- Base SAS is very helpful for people who are proficient in SAS programming.
- SAS Enterprise Miner is very helpful for people who are not so proficient in SAS programming.
- Using SAS Enterprise Miner you can develop complex Machine Learning algorithms.
- Accessing the data from the database directly.
- Speed of response for SAS codes.
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I will opt for ease of using it. SAS Enterprise Miner enables any individual to become proficient in advanced analytics.
SAS is used to gather and analyze data at my company.
- It allows user to view data using different graphs and charts.
- it allows user to export and print data in several ways.
- It allows user to import large amount of data easily.
- Navigation needs to be easier.
- It's expensive for a small company.
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SAS is well suited for a large company that analyses data every day and shares it with their users. For a small company, SAS Analytics maybe redundant and expensive.
- So far, SAS is the best tool for me to manipulate and analyze big data (I also use R and SPSS). It can handle enormous data files and the number of records is generally limited to the size of my hard disk.
- It comes with PROC SQL procedure which allows me to perform SQL queries on the SAS data files. With only SAS, I can do whatever I need to my datasets.
- Although sometimes writing SAS codes is a bit tedious, its Macro procedure allows me to simplify my work. I also can save the codes and run them periodically.
- The learning curve is much steeper compared to the other analytics softwares. But it is such a powerful tool that once you learn it, you will love it.
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It depends on how much knowledge my colleague has on data analytics and how much time he/she can devote himself/herself to learning a new software. If he/she is relatively new to data analysis and cannot spend a long time learning SAS coding. I would recommend him/her to use SPSS which has a very simple point and click interface. If he/she has data warehousing/SQL experience before and wants to dig deep into data, he/she probably is a good starter to learn data mining through SAS.
SAS Advanced Analytics Scorecard Summary
About SAS Advanced Analytics
SAS Advanced Analytics is the company's suite of applications and modules for advanced statistical analysis and predictive modeling. Products from the suite are available a la carte or in bundles, such as SAS Analytics Pro, which offers an alternative to mixing and matching software by combining Base SAS, SAS/STAT, SAS Studio, and SAS/GRAPH into one desktop package.
Categories: Predictive Analytics
SAS Advanced Analytics Competitors
SAS Advanced Analytics Technical Details