SAS Viya Reviews & Insights

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.

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, 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 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.

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

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.

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.

It is being used for data visualization with quick and highly responsive dashboards.

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 best for preforming advanced analytics for personal exploration.

SAS is used to gather and analyze data at my company.

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.

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.

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.

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.

I will opt for ease of using it. SAS Enterprise Miner enables any individual to become proficient in advanced analytics.

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.

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.