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SAS Viya Reviews and Ratings

Rating: 10 out of 10
Score
10 out of 10

Community insights

TrustRadius Insights for SAS Viya are summaries of user sentiment data from TrustRadius reviews and, when necessary, third party data sources.

Pros

User-Friendly Interface: Users have consistently praised the user interface of SAS Advanced Analytics, with many stating that it is one of the easiest they have used. This has made it convenient for professionals to self-learn and navigate through the software without much difficulty.

Accessible Web Interface: The web interface of SAS Advanced Analytics has been highly appreciated by reviewers for its accessibility. Users can access and use the software from any computer anywhere in the world, allowing them to produce analyses on-the-go.

Wide Range of Simulation Options: Reviewers have commended SAS Advanced Analytics for offering a wide range of options for simulations. Many users consider these simulation capabilities to be world-class, providing them with ample flexibility and versatility in their analytical work.

Reviews

11 Reviews

SAS Advanced Analytics Review

Rating: 8 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Pros

  • Easy-to-navigate drag and drop display.
  • Great visual dashboards.

Cons

  • Price point was too high given the level of use we would anticipate.
  • More comprehensive training.

Likelihood to Recommend

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.

YD
Yoni Dvorkis
Lead Data Scientist in Information Technology at Atrius Health (1001-5000 employees)
Vetted Review
SAS Viya
2 years of experience
View profile

A good tool on advanced analytics

Rating: 7 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Pros

  • 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.

Cons

  • 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.

Likelihood to Recommend

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.

RB
Rishi Bavishi, CSSGB, CAPM
Forecasting Analyst in Professional Services at Hilton (10,001+ employees)
Vetted Review
SAS Viya
1 year of experience
View profile

Why I like SAS

Rating: 10 out of 10

Use Cases and Deployment Scope

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.

Pros

  • 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

Cons

  • No needed improvements. Company continues to add more capabilities each year

Likelihood to Recommend

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

AT
Arthur Tabachneck
CEO in Research & Development at Analyst Finder, Inc. (201-500 employees)
Vetted Review
SAS Viya
44 years of experience
View profile

A Look At a New Way to Analyze Visual Data

Rating: 9 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Pros

  • 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.

Cons

  • 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.

Likelihood to Recommend

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.

VU
Verified User
Employee (51-200 employees)
Vetted Review
SAS Viya
3 years of experience

SAS Visual Analytics review

Rating: 8 out of 10
Incentivized

Use Cases and Deployment Scope

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

Pros

  • Good data preparation tools
  • Well written code with few critical errors
  • Responsive customer support

Cons

  • 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

Likelihood to Recommend

Excellent for analytics of massive amounts of data and highly responsive dashboards. Less suited for traditional table like BI reporting.

SP
Sanjeev Pulapaka
Director, Application Architecture and Programming in Information Technology at ICMA-RC (501-1000 employees)
Vetted Review
SAS Viya
1 year of experience
View profile

SAS for Advanced Analytics

Rating: 8 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Pros

  • 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.

Cons

  • 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.

Likelihood to Recommend

SAS Analytics is best for preforming advanced analytics for personal exploration.

RW
Remy Welch
Consultant in Information Technology at Deloitte (10,001+ employees)
Vetted Review
SAS Viya
3 years of experience
View profile

SAS Analytics review

Rating: 6 out of 10

Use Cases and Deployment Scope

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

Pros

  • 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.

Cons

  • Navigation needs to be easier.
  • It's expensive for a small company.

Likelihood to Recommend

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.

VU
Verified User
Analyst in Information Technology (501-1000 employees)
Vetted Review
SAS Viya
1 year of experience

Tried and true, but hard to justify the cost

Rating: 2 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Pros

  • Data transformations
  • Processing large datasets

Cons

  • No big complaints, pretty robust functionality

Likelihood to Recommend

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.

BK
Bethany Klebanov
Sr. Manager Global Business Analytics in Sales at Go2Market Analytics, Inc. (10,001+ employees)
Vetted Review
SAS Viya
19 years of experience

SAS Analytics: Review

Rating: 7 out of 10
Incentivized

Use Cases and Deployment Scope

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.

Pros

  • 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.

Cons

  • Accessing the data from the database directly.
  • Speed of response for SAS codes.

Likelihood to Recommend

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

VU
Verified User
Analyst in Marketing (11-50 employees)
Vetted Review
SAS Viya
3 years of experience

SAS Analytics - They are #1 for a reason.

Rating: 9 out of 10

Use Cases and Deployment Scope

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.

Pros

  • Predictive Analytics
  • Business Intelligence
  • Report Automation
  • Statistical Analysis

Cons

  • Expanded point and click options under the data tab.
  • Better resource information to help with circumstantial issues (i.e. graphing).

Likelihood to Recommend

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.

NO
Nathan Och
Analytics Specialist at Array Services Group (501-1000 employees)
Vetted Review
SAS Viya
3 years of experience