SAS Enterprise Guide is an intuitive statistical analysis solution that enables users of all backgrounds to engage in statistical analysis.
Product | Market Share (%) |
---|---|
SAS Enterprise Guide | 15.9% |
Alteryx | 24.1% |
Alteryx Designer Cloud | 10.8% |
Other | 49.2% |
Type | Title | Date | |
---|---|---|---|
Category | Data Preparation Tools | Aug 28, 2025 | Download |
Product | Reviews, tips, and advice from real users | Aug 28, 2025 | Download |
Comparison | SAS Enterprise Guide vs Alteryx | Aug 28, 2025 | Download |
Comparison | SAS Enterprise Guide vs Bright Data | Aug 28, 2025 | Download |
Comparison | SAS Enterprise Guide vs Altair Monarch | Aug 28, 2025 | Download |
Title | Rating | Mindshare | Recommending | |
---|---|---|---|---|
Alteryx | 4.2 | 24.1% | 89% | 82 interviewsAdd to research |
Toad Data Point | 4.5 | 7.3% | 100% | 5 interviewsAdd to research |
Company Size | Count |
---|---|
Small Business | 3 |
Midsize Enterprise | 4 |
Large Enterprise | 12 |
Company Size | Count |
---|---|
Small Business | 37 |
Midsize Enterprise | 28 |
Large Enterprise | 137 |
Users can create and deploy customized tasks and dynamic content that best meet their needs. Interactive content can easily be shared on the cloud and the internet.
Benefits of SAS Enterprise Guide
Some of the benefits of using SAS Enterprise Guide include:
Reviews from Real Users
SAS Enterprise Guide is a statistical analysis tool that stands out among its competitors for a number of reasons. Two major ones are the solution’s intuitive nature and the suite of functionalities that it offers. SAS Enterprise Guide makes it easy for users who lack a background in statistical analysis to create workflows. The solution enables users to customize and configure queries without requiring them to have a background in coding. SAS Enterprise Guide has a wide variety of functionalities. It is highly flexible and gives users the ability to complete many different tasks.
The head of analytics at a communications services provider writes, “I think that the ease of use is the most valuable feature. I know SQL. I even taught SQL. But new people who come to the tool without in-depth knowledge of SQL or people who do not have an analytics background can still use the tool. It is very easy for these new users to climb the learning curve using SAS Enterprise Guide because of the way it was created with ease-of-use in mind. It is well-oriented to the business user. In no time new users are able to create workflows. Obviously, it is best if they have some basic knowledge of how things work in doing analysis — like the concept of joins, data profiling, and maybe some other SQL-related concepts. But the key here is they do not need to know how it is coded or the exact commands. All the features are available within Enterprise Guide through a drag-and-drop interface so queries can be built without extensive knowledge of how that works behind the scenes. The ease-of-use makes the tool valuable even for someone who is near the beginner level.”
Monica B., an SAS Application Architect at a computer software company, writes, “It has a lot of functionalities. We can build ETL processes. There are clients who are using SAS Enterprise Guide to build ETL processes. They have a SAS-based program that is scheduled to run at a certain frequency to produce some reports for the business. It is a very useful tool for ETL unit tests and functional tests. You can also do data science projects in SAS Enterprise Guide by using different statistics. During my MBA, we used SAS Enterprise Guide for our statistics course.”
Canary Islands Statistics Institute
Author info | Rating | Review Summary |
---|---|---|
Data Engineer at Ministry of Health New Zealand | 4.5 | No summary available |
Data Analyst at a financial services firm with 10,001+ employees | 3.5 | I use SAS Enterprise Guide primarily for data analysis and modeling. While it offers valuable server access, its stability issues and limited visualization features need improvement. Despite using similar products, I appreciate not needing extensive Python for data handling. |
IT Administrator with 1-10 employees | 4.0 | No summary available |
Data Scientist at a tech services company with 1,001-5,000 employees | 3.0 | In the banking sector, I use SAS Enterprise Guide for data analytics and modeling, finding it valuable for data engineering and predictive analytics, though it lacks advanced modeling support and community resources compared to Python's extensive open-source solutions. |
Business analyst at BB seg | 4.0 | We primarily use SAS Enterprise Guide for creating views and filters, deploying it on-premises. The query builder feature is its most valuable aspect, though the solution's stability could improve. We have not used or considered other solutions. |
Senior Manager, Data Science and AI / ML Manager at a tech vendor with 10,001+ employees | 3.5 | No summary available |
Head of Customer Intelligence & Research at a financial services firm with 5,001-10,000 employees | 3.5 | No summary available |
Advisor at KPMG | 4.0 | No summary available |