QuickSight vs SAS Visual Analytics

Amazon QuickSight has received positive user reviews for its ease of use, intuitive interface, and quick data visualization capabilities. Users find it simple to connect to data sources, create dashboards, and generate insights. The drag-and-drop functionality and pre-built templates make it accessible to users of all technical skill levels. QuickSight's strengths include its integration with other Amazon Web Services (AWS) products, such as Amazon Redshift and Amazon S3, allowing for seamless data analysis. It also offers advanced features like machine learning-powered insights and natural language querying, providing users with deeper analytical capabilities. Compared to similar products, QuickSight is praised for its cost-effectiveness and scalability. Users appreciate its pay-as-you-go pricing model and the ability to handle large datasets without performance issues. However, some users have expressed concerns about the limited customization options and the lack of certain advanced features found in competing products. Overall, Amazon QuickSight is well-suited for businesses and organizations looking for an easy-to-use and affordable business intelligence solution. Its intuitive interface, integration with AWS products, and scalability make it a valuable tool for data visualization, analysis, and decision-making.

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.