Processing large datasets is much faster than traditional disk-based processing as the computations are performed in memory (RAM). It also supports advanced analytics like regression, decision trees, clustering, and machine learning algorithms. We have built a regression model to identify loan defaulters by analyzing bureau data. It is easy to use for experienced users and has good customer support as well. It can also be easily integrated with SAS Visual Analytics and SAS Enterprise Miner. Review collected by and hosted on G2.com.

The only dislike I want to mention is its high licensing cost and infrastructure requirements. Review collected by and hosted on G2.com.

Graphical representations and statistical analyses Review collected by and hosted on G2.com.

Many cost. no one can purchase due to cost Review collected by and hosted on G2.com.

Availability of automated analytics.

Cost effectiveness of the product.

Reliable forecasting and reporting tools.

Enhanced model deployment technology.

Customer care and support services are available and proactive.

Ease of use as the product does not require any form of training.

Availability of drag and drop features. Review collected by and hosted on G2.com.

Honestly speaking the product has no notable faults i highly recommend it. Review collected by and hosted on G2.com.

Sas in memory statistics is useful in tracking the amount of memory used by SAS programs and data sets. It is also used to identify memory leaks and used in troubleshooting performance problems as well. Review collected by and hosted on G2.com.

Sometimes it's difficult to interpret the output of sas in memory statistics. It's also sometimes difficult to identify the root cause of memory problems. Review collected by and hosted on G2.com.

One of the aspects I adore about SAS Visual Statistics is its seamless integration with other SAS products. The ability to leverage the power of SAS Visual Analytics and SAS Enterprise Miner in conjunction with Visual Statistics creates a comprehensive ecosystem for end-to-end data analysis. This integration allows for a more holistic approach to extracting insights and making data-driven decisions. Review collected by and hosted on G2.com.

One of the downsides of SAS Visual Statistics is the potential vendor lock-in. As it's part of the SAS ecosystem, organizations that heavily rely on SAS products may face challenges if they consider migrating to alternative solutions. This limitation can restrict flexibility and limit the range of available options, particularly when there is a need for interoperability with different platforms or data sources. Review collected by and hosted on G2.com.

Easy to understand the Datas especially numbers to predict and forecast. Review collected by and hosted on G2.com.

Learning might be difficult if not already experienced on SAS tools Review collected by and hosted on G2.com.

It is a great tool to build a model, even for a non-cs background person. It has an easy-to-use interface and is made for everybody. It is an excellent tool for quick modelling. Without extensive coding, we can generate model AUC comparison reports and charts from the user interface. In a nutshell, it is a great tool for quick modelling Review collected by and hosted on G2.com.

It has limited scope as it cannot handle skewed data, and the backend process and internal calculation are unclear, thereby not very useful when building a complex solution. It has minimal data cleaning and visualisation capability Review collected by and hosted on G2.com.

Cloud storage with this we can execute program faster. Review collected by and hosted on G2.com.

Nothing, mainly it is limited to single machine not for LASR, HPA. Review collected by and hosted on G2.com.

Wide array of tools for data visualization and decision making is available for user. The reporting of data is simple and lucid. Integration is simple. Review collected by and hosted on G2.com.

Debugging frequency could be lesser. Customization could be better. Price point could be worked upon Review collected by and hosted on G2.com.

SAS Visual Statistics helps create interactive predictive models with data from the retail industry and share it with my team members to use with minimal knowledge of machine learning. I can gather live data from live systems and feed the data into models for prediction. The model can quickly identify outliers and problematic data points, which could help improve model performance. Review collected by and hosted on G2.com.

SAS Visual Statistics is not an open-source tool that limits its capabilities. I often have to turn down an idea as I cannot reconcile my approach due to my inability to understand the calculations behind the modelling process. In the era of explainable AI, tools like SAS Visual Statistics will have to make necessary changes to adapt to changing demands from users. Review collected by and hosted on G2.com.