SAS Data Science Programming Reviews - Page 12

It is very helpful for all types of projects. Review collected by and hosted on G2.com.

It worked well for me. I never had issues. Review collected by and hosted on G2.com.

The visualization modules are powerful, scalable and quite robust. Our team is exploring time series analysis and discovering ways to leverage text analytics in our core ETL processes which is very interesting. Review collected by and hosted on G2.com.

I haven't encountered anything I disliked so far. I feel that the UI is intuitive and controls are straightforward however in a future release, I'd like to know if future integrations with opensource frameworks and programs like python and R will be supported. Review collected by and hosted on G2.com.

SAS Visual Analytics is an excellent tool for creating and sharing dashboards with people with limited technical exposure. This tool seamlessly integrates with Microsoft 365 tools, and daily reports can be transmitted through outlook. This tool has a natural flow, and data visualization reports can be created using its drag-and-drop feature.

Data integration with custom data sources makes life easy as it can be used to make specifically tailored reports. Sharing reports with executives is more straightforward with SAS Visual Analytics. Review collected by and hosted on G2.com.

Installation and using the license for SAS Visual Analytics can be a bit challenging and often requires the help of an expert. Online community support is minimal as this tool is not open source and requires a license to be trained. Review collected by and hosted on G2.com.

SAS Visual Text Analytics helps create value from large textual datasets by extracting information like key relationships, sentiments, context etc. It offers analysis nodes for text parsing, concepts, topics and categories, using which it can customise the model to our needs. SAS VTA is a web-based application, and the user interface is natural and can be used to perform a complete set of operations like model deployment and automation. Review collected by and hosted on G2.com.

SAS Visual Text Analytics struggles with multilingual text, and it isn't easy to build custom models that can vary according to the domain. I tried to upload a custom Tokenizer, but I was not successful. SAP has limited help from community as it is not an open-source tool. 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.

SAS Visual Analytics offers a singular window for developing and automating data extraction and transformation pipelines and creating in-depth data visualisation. This tool can handle extensive data and is well-integrated with Microsoft products.

The geo-tagging capability of data gives additional insight if you are working on retail data. The visual graphs are intuitive and can be handled easily with drag-and-drop functionality. The tool is very smooth to use because of its in-memory processing. Review collected by and hosted on G2.com.

SAS Viya looked a bit complex to me in the initial onboarding phase because of so many options to play with, which I became familiar with eventually. There was little help as this is not an open-source tool, and the community is of little use. Review collected by and hosted on G2.com.

SAS Visual Analytics with the aid of machine learning and natural language, visual analytics enables us to tell comprehensible tales from unstructured data. It makes it easier to create and distribute data insight dashboards that can be easily customised with little to no work and do not require specialised knowledge to comprehend the effects.

The best feature of SAS VA is that it has the capability to automatically detect key relationships and clusters. It can also detect outliers in the data which helps in debugging and identify problematic areas. Review collected by and hosted on G2.com.

Problems arise since SAS is not open source, and there may sometimes be issues with generic tool integration. Compared to alternatives, SAS is a little more expensive, and with new open-source tools on the horizon, it won't be easy to justify the cost. Review collected by and hosted on G2.com.

Its ease of use and ability to see, review, and visualize the data sets is the best in the industry. You never feel as if you are working with a blackbox. Review collected by and hosted on G2.com.

This software has taken a bit too long to come out with the capabilities, due to which we have gotten accustomed to other tools during the catch up period Review collected by and hosted on G2.com.

SAS Visual Text Analytics has many built-in natural language models, which are available as Nodes in the platform and can use to identify information like context, sentiment, topics or key terms in textual data.

This tool can help skim through unstructured data to create insights from large documents.

The device has a user-friendly interface and can be exploited to eliminate human effort. Review collected by and hosted on G2.com.

SAS Visual Text Analytics has a smooth user experience. It offers fantastic potential, but this tool does not have details of the inner workings of the models running in the background. The platform lacks proper documentation about the models used for inference as this is a licensed tool. Review collected by and hosted on G2.com.

This URL-based application is beneficial for creating a dashboard as an output of the ML models produced by business users. Basic and some of the complex preprocessing of the data, like cleaning, manipulation, and validation, can also be done on the same interface page itself. Along with Models, Regular data visualization of the data can also be performed. And can be shared via URL for another business user to view the dashboard without any pre-installation or any sort Review collected by and hosted on G2.com.

This application is primarily ideal only for the structured data source. Only a limited range of model creations, like linear and logistic regression, NN, and Forest, is available. Even though this application combines ETL, data analytics and visualization, extensive data cleaning is not possible in the same interface, as it is suitable only for structured data. Review collected by and hosted on G2.com.