GraphPad Prism vs SAS Visual Analytics

Is GraphPad Prism the real deal or just a statistical mirage? GraphPad Prism is a popular software choice for scientists who need to analyze and visualize their data. Users praise its ease of use, especially for those without a strong statistics background. They appreciate the intuitive interface and the clear explanations provided for each statistical test. The software's ability to generate publication-quality graphs is a major selling point, with users highlighting the wide range of customization options available. For example, one user mentioned using Prism to generate figures for publication in peer-reviewed journals, highlighting its ability to create professional-looking visuals. However, some users have expressed concerns about the software's performance, particularly on older or less powerful computers. One user noted that Prism can be resource-intensive, even on a computer with 8GB of RAM. This can be a significant drawback for researchers who need to analyze large datasets or work on machines with limited resources. Additionally, some users have suggested that the tutorials could be improved, particularly for specific analyses like IC50 calculations. They believe that more real-life examples and detailed explanations would be beneficial. Overall, GraphPad Prism is a powerful tool for scientists who need to analyze and visualize their data. Its ease of use, comprehensive statistical analysis capabilities, and ability to create publication-quality graphs make it a strong choice for researchers. However, its performance on older computers and the potential for improvement in its tutorials are areas that could be addressed in future updates. GraphPad Prism is most suited for scientists who are looking for a user-friendly software that can handle a wide range of statistical analyses and produce high-quality graphs for publications.

SAS Analytics is a versatile business intelligence and analytics tool that empowers users to explore and understand data through interactive data visualizations. Many users who reviewed data analysis said that, coupled with the power of predictive analytics, the platform offers a plethora of graphics options — charts, graphs and dashboards — with deep-dive capabilities, such as filtering, to zero in on pertinent business data. Many users who reviewed functionality and data preparation said that, possibly because of its capable ETL engine and in-memory architecture, data processing speed is very high and reports load faster. A majority of users who reviewed data connectivity said that the tool is efficient in pulling data from multiple sources for data modeling and analysis. On the flip side, quite a few users who reviewed functionality said that the platform’s integration with Python and R is still in the development stage and this limits its functional scope. Some users who discussed user-friendliness said that the processes are not the most intuitive — errors and warnings in logs are misleading, and new users may find adoption difficult. Though the industry scope of user tutorials is limited, a majority of users said that the steep learning curve of the platform is sufficiently addressed by training. For many users, its cost-prohibitive licensing plans caused them to not consider it their first choice when it came to purchasing a BI solution. Overall, SAS Visual Analytics is a versatile tool with fast data processing capabilities and strong visualizations to generate reports for insightful data analysis.