SAS Enterprise Guide Reviews

“perfect tool”

Pros

With a graphical interface at its core, this tool supports statistical modeling, analysis and reporting with minimal coding effort. Workflow creation is simplified through block-based data manipulation functions. The interface is organized into analysis flow, results, tables and log sections, where each serves a clear purpose in managing work and reviewing outputs. Execution details and errors are easily tracked through the log section.

Cons

Report generation is another area where I see limitations, as the default output is not visually polished enough to share directly with teams. Because of that, I often have to export data into third-party tools for better formatting and visualization which adds extra time to the overall workflow.

“Predictive analytics solution”

Pros

Data management and statistical analysis become more easy through a clean and simple interface. Workflows can be built by dragging and connecting processing tools, reducing dependency on coding. Although SAS language is not strictly required for complex analysis, it becomes useful for customization and faster execution. The platform scales effectively with large datasets and integrates smoothly with other tools from the same vendor, expanding analytical capabilities.

Cons

Bringing it into a company comes with a significant licensing cost and given that there are open-source tools capable of performing roughly similar operations to SAS Guide, it would make sense to reconsider lowering the license price. The license renewal process is also quite tough. At a certain point, the software on the analyst's machine simply stops working and the PC has to be handed over to the company's IT department so they can update the license. As far as I know, that update system has never really changed and it feels overdue for a review.

“good to go...”

Pros

Handling data management, statistical analysis and reporting without coding is possible through drag-and-drop process flows. This approach improves accessibility for users at different experience levels. Compared to tools like SAS Studio, this feature stands out for its simplicity and usability. Code-based analysis remains available for deeper customization and faster execution when required. Strong performance is maintained even with large datasets and machine learning algorithms are also supported.

Cons

The only real drawback I see with this product is the price. That is not a minor issue for small and medium-sized businesses which may end up choosing open-source tools to carry out data analysis at no cost. In my opinion though, the evaluation should take into account SAS's high performance which is better than free alternatives, as well as the dedicated support provided by the company something open-source products usually do not offer.

“Workflow automation platform”

Pros

A powerful and complete statistical data processing solution, this tool efficiently handles large volumes of data and remains easy to use for basic analysis through built-in nodes with predefined functions. Adding programming enables more advanced analysis, including complex forecasting models tailored to business needs. Support for multiple file formats enhances flexibility making it suitable as a central data hub for diverse data sources. For example, in banking, ECAI ratings can be used to develop shadow rating models before final analysis.

Cons

One weak point is the graphical analysis side. While the software is very detailed when it comes to presenting the results of the statistical analyses performed, it is less strong in terms of charting detail. Creating graphs through programming can be tough and in some cases you need to use too many options within a data step just to get one extra level of detail in a chart. Because of that, the graphs are not always simple to adapt to specific situations.

“Statistical workflow hub”

Pros

An advanced statistical data analysis platform suitable for users with varying experience levels, it allows workflow creation by connecting preconfigured tools for tasks ranging from data joins to full model estimation. Alongside built-in features, SAS code enables more complex and customized analysis. Efficient performance is maintained even with large databases and results can be exported in multiple formats for organizational sharing.

Cons

The downside of EG is mainly the cost, along with the fact that to take full advantage of the SAS suite, you often need additional connected software products with licenses that are not cheap.

“Data processing is easy now”

Pros

A strong solution for building data processing and analysis workflows quickly, this tool leverages drag-and-drop nodes for efficient task execution. Workflow automation supports recurring analyses such as weekly or monthly reporting. Large datasets are handled effectively while statistical tools help identify patterns and develop predictive models. Standard nodes cover common needs and customization options are available for more advanced analytical requirements.

Cons

Getting the most out of it does require a certain level of experience. To fully master all the features, dedicated training is needed, usually through SAS Institute courses which adds extra cost on top of a license that is already quite expensive.

“great for my team”

Pros

When it comes to data analysis and statistical model development, this is a very high-performing tool that makes it simple to build your own analysis workflow. You can work with it through nodes or through the more traditional SAS programming approach which I personally recommend and which also includes some SQL commands. It adapts well to many different situations and throughout my career I've seen it used by financial institutions, asset management firms and even large energy distribution companies to cover a wide range of needs, from estimating models and building scenarios to monitoring the current state of the business, helping organizations make truly data-driven decisions.

Cons

It's an excellent tool for data analysis and processing but table navigation is where it falls short especially with very large datasets. When you need to display results on screen, it's usually better to use a PROC rather than applying filters directly to the displayed table since that approach ends up being much faster than navigating the table itself.

“Statistical modeling system”

Pros

Even junior analysts can handle fairly complex statistical data analysis with this tool without too much difficulty. The option to work either through "nodes" or with traditional SAS code makes it suitable both for beginners and for more experienced users who need extra precision and control. Another strong point is performance, since the processing runs on external servers with more computing power than the local machine where the software is installed, analyses stay particularly fast even with large datasets. On top of that, the machine learning capabilities make SAS a very valuable solution for the kinds of challenges risk analysts are likely to face going forward.

Cons

Overall, I consider the software complete and well organized. I do not really feel that any essential functionality is missing although it could be useful to add a few features that make life simpler for programmers, such as drag-and-drop file import/export. In substance though, I do not see any major areas that require improvement.

“Advanced analytics toolkit”

Pros

With just a few steps, this software lets you work with and analyze large amounts of data for reporting and statistical modeling purposes. Its biggest advantage is how simple it is to use, you can build programs through nodes and also customize those nodes by writing standard SAS code inside them. The code itself is not especially difficult to learn and, for less experienced users, the documentation available on SAS websites is very helpful. On top of that, the platform supports statistical modeling both with standard techniques and with more advanced machine learning methods.

Cons

Dashboard customization is somewhat limited and that can slow down the workflow. It also takes a noticeable amount of time to process very large tables. While node-based programming is convenient for junior users, it may feel restrictive for a senior analyst who needs to carry out more complex analyses.

“Business intelligence platform”

Pros

SAS is an excellent tool for processing and analyzing large volumes of data with great speed and a fair level of simplicity. Using its proprietary language which is not especially difficult for the routine tasks most analysts handle every day, it allows you to build different kinds of statistical models, including machine learning models. These are very useful for helping companies make informed, data-driven decisions or, in my specific case, manage risk effectively. On top of the native coding language, the software also supports SQL queries and lets you export processed data in several formats which makes sharing information much easier in structured organizations such as large banking institutions.

Cons

One of SAS's biggest weaknesses is definitely the cost. The software is quite expensive and that can be a real burden for smaller institutions. Beyond the license fee, you also have to factor in the cost of SAS servers if you need to process very large amounts of data. On top of that, handling more complex tasks efficiently requires a good command of the code especially things like macros which can lead to additional staff training costs.

“High cost limitation”

Pros

The way it displays data is well done.

Cons

The price is high and connecting it with other open-source software is difficult.

“Easy workflow analysis”

Pros

Low-code setup and drag-and-drop tools have been really useful for handling a lot of the tasks I regularly deal with as a data analyst.

Cons

Getting around the platform does come with a bit of a learning curve so it can take some time to feel fully comfortable using it.

“User-friendly upgrade”

Pros

After using SAS since 1981, Enterprise Guide feels like a huge improvement in terms of user-friendliness compared with how things used to be.

Cons

Coming from the old-school, manual way of doing things, I sometimes have to override certain automated features when I want more flexibility.

“Reliable processing solution”

Pros

The platform delivers great data security, runs fast and efficiently and benefits from a large user community which makes it easier to find help and shared knowledge.

Cons

The biggest downside is the high cost. It also feels overshadowed by Python because of its open APIs and a lot of companies seem to be moving away from SAS for that reason.