SAS Predictive Analytics Reviews

I have been using this solution in different companies and have used all of the tools like SAS Enterprise Guide and SAS Studio. The Studio is where predictive analytics is done.

My use of this solution has been for data analytics in different domains, such as for providing quotes in the financial industry.

I do not deal with the core administration. I typically use it for programming and analytics.

The most valuable features are forecasting and reporting. We have used these features to produce predictive analytics reports for retail clients.

The dashboard could be made easier to use. I think that SAS BA represents an evolution of the product in this regard.

I think that this solution should be more compatible with other software, including open-source solutions.

If SAS were more flexible in terms of licensing then that would be good, because it costs more than other solutions.

I would like to see more flexibility in the interface so that a person at the managerial level can also make use of it in a basic way.

I have been using SAS Predictive Analytics for the past 12 years.

I have never had issues in terms of scalability.

I have rarely been in contact with technical support. There are organizational tools and manuals available so we've always tried to handle problems by ourselves, rather than use an external support team.

I have done some predictive analytics with relational databases like SQL Server and Oracle. The interface is different for each of them, but the base of everything is SQL so the main differences are the interface and the syntax.

I think that it requires some basic knowledge for a person to install it, but otherwise, it is straightforward. For somebody with experience, it will be okay. However, there is other software, such as Tableau, that is easier to install than SAS.

Wherever I have worked, there have been sufficient manuals and training to help install it without assistance from a third-party integrator or consultant.

This is a good solution, although I consider other software as competitive and more user-friendly. SAS is not for everybody. When it comes to data quality and data integrity, SAS is superior, but when it comes to user-friendliness, there is other software that behaves better.

I would rate this solution a seven out of ten.

I have used Predictive Analytics for analyzing email-related data and data for healthcare products. Some of these products include:

• Water quality management
• What areas are going to be affected by bad water quality
• Pollution control
• Determining which areas are going to be polluted and with what types of pollution

The most valuable feature is its flexibility and the ability to integrate with SAS. It is easy to integrate with open-source technologies like R or Python.

I like the drag and drop interface. We can select datasets using drag and drop, for example. 

We use the classification and regression functions for building models from emails.

There are not many people deploying models using this solution, which is a problem.

I have done some cross-development and have found that when I am building models with the open-source software, the accuracy is better. For categorical data, the models built by SAS Emailer are very complex compared to those built by the open-source version.

Technical support could be improved because they take too long to answer our queries.

Models that are created are a block box, and you can't see the details.

We have been using this solution for one year.

The scalability is good. We have more than thirty users.

Technical support takes too long when we make an inquiry.

We have four or five people who are in charge of maintaining this solution.

For some of the things that we do, we use this solution in conjunction with SAS Forecast Studio.

This is a good solution, although the speed of the technical support needs to be improved.

I would rate this solution a seven out of ten.