SAS Enterprise Guide Reviews

We use SAS Enterprise Guide for ETL and data processing.

My team is not using SAS Enterprise Guide extensively, but I imagine it's being used heavily for processing a lot of workloads in my company which has been an improvement.

We are using SAS Enterprise Guide on a basic level and the Pro SQL and other procedures within it are the most useful right now. Additionally, it has a wide feature set and capabilities

We don't use SAS Enterprise Guide that much here because we haven't explored some of the statistical modeling capabilities. However, I do not think SAS Enterprise Guide provides all the machine learning features that we want. Those would be separate products from SAS, such as SAS Buyers or any of the other solutions, which will give us the capabilities that we are looking for. 

I have been using SAS Enterprise Guide for approximately 10 years.

SAS Enterprise Guide's stability is fantastic.

The scalability of the SAS Enterprise Guide is good.

We have several hundred users using this solution in my organization. We have data analysts, data scientists, developers, and other roles using it.

We do not have plans to increase usage because we only use the solution for a particular purpose.

I have not contacted the support from SAS Enterprise Guide.

We have seen a return on investment from using SAS Enterprise Guide.

SAS Enterprise Guide does what it does quite well, we use it for a particular purpose. We haven't explored some of the other opportunities with a lot of the statistical modeling and other options that it provides, but those would be nice to have.

I would advise others to start with small use cases and then scale up. It will scale very well to many of the functions that you want in data science and data engineering.

I rate SAS Enterprise Guide a seven out of ten.

The reason I wouldn't rate Enterprise Guide as 10 is that it is lacking some features that we are looking for.

We use Tableau for visualization and SAS EG for analysis. SAS EG is more useful for analysis, while Tableau is better for visualization.

In Daman, I had used the data module, where you can join the table and take whatever data we require for our work. You join tables and create columns as you wish, then analyze data in various ways depending on what the problem is. We used it to detect fraud, abnormalities, anomalies, abnormal trends, etc. It's also good for exporting and importing tables.

Now that I have experience with Tableau, I think the visualization part of SAS EG could be more user-friendly and easier to use. Tableau is very easy to use. It just does a lot of work by itself, including color schemes. I think that could be incorporated easily into SAS EG, which would make it a much better product. Then you would not need Tableau.

Tableau just adds a few visualization aspects onto it, but it doesn't have powerful analytics like SAS. You can join a number of tables in SAS. That's what I find very useful. You can keep on doing that. You can just change one and get another report. You can save the script and run it again. SAS has all kinds of useful features, so I think it is very good for analysis.

We actually saved millions of dirhams on licensing data, just by sitting here and getting data for a month. Now they're developing their routine using it as if it's Excel. I need to develop it because they don't really have it here. They were only using Tableau, but Tableau basically just sums up the analysis. It cannot do certain analyses. Mostly it's summing up and finding the fraction and percentage. You can easily do that, but it is a bit tricky to use because you cannot join so many tables and you cannot double it. That kind of function is not there in Tableau. That is the main drawback in Tableau.

SAS is very good actually. It's not really user-friendly and it's difficult to configure as well. It's difficult to configure the graphs and charts. In Tableau, it's really easy to do that and I think that can easily be developed in SAS, considering that there are complex analysis functions already provided by the solution.

It should also be easy to integrate any database like PostgreSQL. I have spent more than one hour on more than one occasion trying to connect it, but it did not work. I think that should not be the case. It should be just really comfortable to do this.

I worked at the Daman insurance company for four years and they used SAS EG all the time. Now I am at another company that uses both SAS EG and Tableau. 

The stability is quite good. However, I found out that we don't have a direct connection to the database. The company I'm working at now doesn't have a data warehouse. Data needs to be exported into Excel and then re-imported into SAS EG. That is going to be a little tricky because we really want all the rules to be imported. That's an issue. I don't know how deep the problem is, but there's a software limitation in importing so many Excel files and then joining them to the database. In Daman, where I worked earlier, we had direct connectivity to the database, besides the fact that we had a data warehouse.

Right now, I don't know. I feel that before we build anything, we need to validate the data. Validating the data can be very tough and tedious. For instance, the other day I took one year and six months of data from a hospital and I'm now importing it one month at a time. It's very tedious. They needed data for their whole warehouse.

Then it would be very useful to have a lot of people working on it. It could take off nicely. First, you need to know that the data is correct, though. Right now, we don't know that the data is correct. It is very important to clean the data and ensure that your work is providing data which is really what you're trying to measure. That itself takes some time.

I import data each month and check that the number matches. I check that the net amount is correct. It all takes time. I know it's true if somebody else gets the same answer. Importing is where the issue is, though. That is where I'm having trouble because sometimes I find there's only partial importation.

I insert an extended table in the columns and rows with good formatting so that it doesn't miss anything. I think that that works well.

I have contacted them. We are currently having a problem because I have two databases. One is a pharmacy and I am trying to connect to the pharmacy database. They're allowing me to connect to their line. However, SAS EG is not connecting to the database on the pharmacy side. There are two sides, the pharmacy-side, and the hospital-side. On the pharmacy side, their data is available on the screen, but it's not connecting.

We've tried them both several times. They came online and tried on their end also. Everybody tried to find history, but they were just getting stuck. They went through so many stages. Importation was very successful, but trying to get the last days did not succeed. There was some issue there. They saw this issue in every pharmacy database that was directly connected to Tableau. They usually manage their data with Tableau and so I had to export it from there.

The initial setup was simple. Once you understand the concept of their scale, how they join, and the logic behind the whole thing. If you know how to join tables this shouldn't be difficult. It's not complex. The tables are complex, but the underlying principles are not complex.

We had a three-day introductory course only. It doesn't tell you every unique case. There are a lot of things, but you can figure it out. I think you start doing it right away, but then you can go to YouTube and see someone use it as well.

I've got a first degree in mathematics, so I understand this kind of concept easily. That is my background. Still, I need to know how this works. We figured it out from YouTube and friends. Now I understand the product well.

When I joined this company, they did not have SAS at that time. They did not know what SAS was. They only had Tableau. I told them to let me try that with that. I taught myself Tableau and could use it because I knew that the concepts are the same. The logic is the same. Boolean algebra is the same. Just like that, I started using it. Within two hours, I started using Tableau.

Now I have SAS also, so I am using both now.

I would rate it quite high, but because I don't have experience with other similar solutions, I cannot say how good this is. I have nothing to compare it to, as my experience is limited to SAS EG and Tableau. For my purposes, it has been great, but I don't know how well it can find patterns by itself with machine learning.

I read in the newspapers and the internet that so much more is doable. The preliminary analysis could be done with a machine. Right now we have average, mean, median, but machine learning could provide much more.

From that, instead of looking at thousands of lines, one could just look at a few graphs and see where you should dig further into. Perhaps you could have a video or dashboard.

I don't mean generic dashboards. I mean a dashboard, which you can then pull up and down to see what else is there. They have that technology these days. I think it should be possible without stretching too much.

I would rate this solution as seven out of ten.

I am currently using this solution for testing purposes. I am working for a pharmaceutical company in Belgium, and we are building a data warehouse by using SAS Data Integration Studio, and we are using SAS Enterprise Guide to test our development. We are building Enterprise Guide projects by using query builder, filters, and other things. We have also built stored procedures. Sometimes, we also write SAS base code to perform unit tests after development and to do some sanity checks to respond to UAT questions. Overall, we are using the majority of functionalities of SAS Enterprise Guide. 

A client has used SAS Enterprise Guide to build an ETL process that involves extracting and transforming the data and producing reports. These reports are very crucial and useful for their monthly and daily activities. By using SAS Enterprise Guide, they are able to deal with end-to-end processes for their business.

Filter and sort query builder is valuable. The ability to do advanced SAS programming is also a useful feature because we can do anything by using Enterprise Guide. 

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 statistic course.

To query the data, there are many solutions such as SQL, but these tools are only a part of the integration. They are only useful for querying the data and require knowledge of SQL, so they are not suitable for business users. SAS Enterprise Guide can be very easily used by business users to filter and sort the data and build queries. It is not necessary to have coding skills to use SAS Enterprise Guide. For this reason, it is attractive for businesses.

Our data warehouse is built on the Netezza database. We have SAS BI, and we populate the Netezza database. When we have tables with, for example, a hundred million rows in Netezza, SAS Enterprise Guide doesn't work. It doesn't return any results. It works for around 30 to 40 million rows, but it is not working for anything more than that. This issue is only with the Netezza database. With Oracle, it is quite good. They can improve its performance with the Netezza database.

There should be one unique tool that includes SAS Data Integration Studio and SAS Enterprise Guide for more integration capabilities. With SAS Enterprise Guide, it is not possible to create connections and libraries and build transformations that can be used for other projects. This tool should have all capabilities that SAS Enterprise Guide does not have. Such a tool would be perfect because it will be used by developers and business users at the same time.

In addition to the integration capabilities, they should also provide more deployment capabilities. There should be an option to easily create SAS packages and export them from one environment to another. There could also be a possibility to connect with R and Python. Open-source tools are hot in the market nowadays, and it would be good to extend its capabilities. 

I have been using this solution since 2005. It has been almost 16 years.

It is very stable. 

It is easy to extend for fast data integration functionalities. We have around 1,000 users. They are developers, business analysts, and project managers.

In terms of usage, my clients don't have any plans to expand its usage.

They are responsive and very good. They respond within a day of creating a ticket. 

It is not quite easy to deploy. When we worked on the SAS migration project, the migration to Enterprise Guide was quite difficult. The deployment duration depends on the project. Generally, it would take a few days to solve all the issues.

For the SAS migration project, we worked with the SAS Belgium team. With their help, it was okay, but it should be easier.

In general, SAS has high prices, which is a reason why some clients don't use SAS solutions. The licensing is on a yearly basis.

I would recommend this solution. It is a very good tool for outputs from different domains, such as ETL reporting, data science, etc. It would be good to bring more functionalities similar to Data Integration Studio so that we have one single tool. 

I would rate SAS Enterprise Guide an eight out of ten.

We use this solution for data manipulation and statistics.

This solution allows for simplified working with large datasets.

The visual interface makes teaching new analysts how to use the tool easy.

I would like to see better Charting in this solution.

We primarily use the product for data analysis and investigations.  

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.  

I think machine learning should be added to the product. It already has virtually everything from the data wrangling perspective. Machine learning concepts could further enhance the user experience and the results.  

The concept of visualization could also be added because, currently, we need to use a separate tool. We use Business Objects for data visualizations.  

Competing products — like in case of Alteryx that is just in trial versions for now — has both machine learning concepts as well as some of the visualization capabilities within the data profiling features. SAS Guide will have to have these features to keep up with competing products and their capabilities.  

If these elements do pan out properly in Alteryx, I may like it better than SAS Enterprise Guide overall. I have a data science background but the more advanced data science features are new in these products and they are very useful in analytics.  

So SAS should work on ML (Machine Learning) features, visualizations, and even more on ease-of-use. It is good but everything can get better.  

I have been working with SAS Enterprise Guide for six years.  

We have not yet had any stability issues with the product. First of all, it is working well. Secondly, on the hardware side, we thought that we need to have more resources, so we did a capacity planning exercise involving SAS. They gave us some recommendations to improve our environment moving forward. We are installing a new setup on new hardware based on those recommendations. This should maintain our current level of stability and maybe enhance performance.

I feel that SAS has a good foundation. It has not given us a lot of problems when it comes to performance. We were being proactive. It works really well in combination with Teradata, but there is a lot of room for performance optimization with both tools.  

Using both platforms — and by that I mean featuring both SAS and Teradata — we do get our data out. In telco, the data volumes are huge, but even though that is the case we do not usually get stuck or experience stability issues.  

There are a lot of ways to get the performance optimization you need from products, get the work done, and delegate your time. It takes evaluation and revisions to accomplish those goals.  

There are many more business users in our organization, but there are only about seven people who really use Enterprise Guide as technical people. We do not see much of a problem with scalability for either group of users.  

Technical support is good. Whenever we have a problem, we have technical support sessions. It can be improved, I believe, but I would say that it is not bad either. It works for us.  

We do use other tools on occasion although we are presently focused on Enterprise Guide as our core in analytics. Ultimately the goal is to get the best results in the easiest way. If that requires changing tools, that may be necessary. Right now we are using SAS along with Teradata.  

The initial setup is a bit complex. For the guest access setup, that is something that we do ourselves. But when it comes to the server installation, that is where we require support from SAS. When it comes to the server installation, the configuration is usually done by SAS themselves. The setup is something that is certainly too complex for business users or people who do not have a technical background. It is usually good to involve SAS even if you are going to an upgrade. It can just make things go more smoothly and keep from wasting time with unnecessary issues.  

We just have one guy for the maintenance of the system. If there is a problem, then he can rely on support. There is only one guy because the product is pretty stable.  

When looking at different tools on the market for data analysis what you need depends on what you want to do. If you have a portfolio within your organization, you may feel that you will need a lot of other tools in addition to make a proper analysis. SAS is a broader solution. It is not just the Enterprise Guide. It has marketing automation and there is even stream processing. Then there is Enterprise Miner. Enterprise Guide is a suite and not just a one-dimensional tool.  

If you feel that you are ready to make an investment and you need the capability of advanced analytics within your organization, you will be able to utilize the whole tech stack with Enterprise Guide. If that is the case, then obviously I think you should go for SAS because it is a more mature and evolved product than most other products. In addition, the opportunities for integration with the SAS platform is really good.  

If you need a specialty architecture, you have Alteryx on one side and you have SAS on the other side. If you do go with Alteryx, then you have a separate campaign management tool and you may not be able to get the full benefit of an integrated solution.  

People considering SAS Enterprise Guide should also look at Alteryx. It is pretty simple. Some people on my team feel that Alteryx is actually much easier to use for what they do and that its interface is much better even if it is similar to Enterprise Guide. The overall availability of different kinds of features is much better in Alteryx.  

I think the first step of evaluating potential solutions should be to look at your roadmap. If you want to go start simple, then obviously you can start with any tool. But if you have a roadmap in place or if you are not a beginner, then I would suggest going for one integrated platform as a suite rather than multiple tools. Having an integrated solution is probably a better overall.  

On a scale from one to ten where one is the worst and ten is the best, I would rate Enterprise Guide as a seven overall. It is a good product but it lacks some important features other products are coming out with.  

I use it for programming. When we import data sets or databases, we work with data management and program scripts, etc. We have its basic license.

We work with large data sets that cannot be handled in Excel. SAS gives us the opportunity and the privilege to work with large data sets. It is very easy with SAS, and it saves time. For example, if I want to use the same data with Excel, it would take a whole day, but with SAS, I can do it in two or three hours at the most.

We are able to work on the server, and I can copy a data set and share it with someone in my team. Similarly, if I want some data from them, I can get it. Being able to work on the server and being able to switch from one user to another is a good thing.

It is reliable and powerful, and its community is very wide.

They should provide more information for the errors or logs. Currently, it gives you just the error message without explaining anything.

I have been working with this solution for two years. I use it daily for my work.

It is reliable.

It is scalable. It can handle large data sets. There is no problem with that.

Currently, we have a team of five people. I have a manager and other colleagues. All of us don't have the same role. We all handle data, but we have different diplomas. I work as an actuarial analyst, statistics engineer, and data analyst.

I am not sure if we have a contact for technical support from them, but there is a big community of SAS.

We used the open-source product R, which is not exactly similar. We switched because it was a part of our strategy to use SAS. In terms of time response, R is not very powerful. SAS is more powerful in terms of data management., and someone who is not very experienced with programming can use the UI.

I was not involved in the initial setup. Its maintenance and administration are handled by IT, but they're not very well-trained in this solution. It is a new one for them, and sometimes, we do get stuck because they are not very experienced with this solution and its features.

It is very expensive. We have a basic license, and there are many features that are not available with the basic version.

You must have a basic background in programming, such as SQL programming, to use it easily.

I would rate SAS Enterprise Guide an eight out of ten.

Using with SAS Grid, data manipulation, preparation, and modeling development.

• Enabled us to remove PC SAS, which reduced risk.
• Takes advantage of our Enterprise SAS Grid.

• The Copy task feature
• Portability with SAS Studio
• User interface and code builder

More bi-directional integration with the SAS Studio suite of tools is needed.

We use SAS EG to manipulate large datasets and prepare them for actuarial analysis with other programs, as well as ad hoc analysis.

SAS EG is a reliable program that consistently performs well when it comes to manipulating large datasets. Furthermore, the process flow and code wizards help keep things well organized so that it's easy to pass on projects to other analysts.

As discussed above, the process flow and code wizards are very valuable as they allow any analyst, even those totally new to SAS, to quickly learn about new projects and get up to speed so that they can start working with it as fast as possible. The base SAS functionality of SAS EG delivers when it comes to consistently handling large datasets and, for the most part, it's not too difficult to write custom code to do whatever you want to do with your data. If things are ever too much, SAS's technical support team is easy to contact and incredibly helpful with any problem.

I realize that this is fairly impractical as a request, given how SAS EG is programmed, but I'd love it to be as quick as base SAS for simpler data queries. The intention of SAS EG is that the SAS commands are executed on a server, so this isn't a very fair comment to make. I do find the online documentation can, at times, be a little difficult to read through and understand and sometimes there aren't a lot of examples to help you understand. I'd love for there to be more examples as well as a summary post of some sort on how to go about interpreting the nuances of how the documentation is written.

SAS has absolutely excellent technical support. I've reached out on multiple occasions for various issues, usually involving how to code something or an error with my code, and always gotten a response back within 24 hours. The technical support staff has always worked with me to ensure that they solve my issue and are very good at what they do; I've never been disappointed, even when asking about an issue with Windows that I was trying to circumvent by going beyond SAS's intended functionality.

SAS has excellent customer service and their products are well tested and perform their intended function, however, they aren't inexpensive. Generally speaking, there is a higher initial cost to obtain a license and then a reduced renewal cost, but you'll be paying the renewal cost for as long as you want to keep using their software programs. SAS is careful to keep pricing a private matter, so it's hard to know if you're paying more or less than other clients for a license. It's also difficult to shop around and price compare as you need to enter into a discussion with a SAS representative to obtain a quote, personalized to you.