QuickSight vs Einstein 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.

Einstein Analytics from Salesforce is a predictive analytics BI tool that uses the power of AI and machine learning to glean insights and create visualizations and reports to drive business decisions. All users who reviewed its analytics capabilities said that it excels at augmented analytics. Many users who reviewed data visualization said that templates and dashboards are easy to customize for deep-dive data exploration. With a range of reporting options and intuitive drag-and-drop functionality, the platform empowers business users to create their own reports without needing to code. Being part of the Salesforce suite, the platform integrates well with other SF offerings, as expected, as well as with external data sources. As for the tool’s data management capabilities, some users said that ETL functions are self-contained in that they replace the need to write code, however others said that data needs to be cleansed before the ETL engine can consume it for data analysis. Commenting on the software’s functionality, around 68% of users said that it is easy to drill down into KPIs with little training in analytics, whereas some users said that the platform is sparse in terms of features and does not have the same reporting capabilities as other Salesforce tools. Mentioning the interface, a majority of users said that it is clean and interactive, though quite a few users said that they preferred the classic version to the new one. A majority of the users who reviewed pricing said that, in addition to expensive per-user licenses, other costs can quickly add up, since implementation is not easy and often requires professional vendor support. Many users who discussed setup said that the platform struggles when processing large amounts of data, and plugins are needed to process heavier data sets, which further compounds costs. Quite a few users said that the platform performs well within the Salesforce ecosystem; however, it does not have the robustness and flexibility of Tableau. Overall, Einstein Analytics is a BI tool with strong out of the box ETL and data visualization capabilities that glean deeper insights into business metrics and seems to be suited for organizations with lightweight data analysis needs or those that already implement Salesforce solutions.