We performed a comparison between Oracle Analytics Cloud and SAS Visual Analytics based on real PeerSpot user reviews.
Find out in this report how the two Data Visualization solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."It has the best feature for data augmentation."
"The solution can scale."
"The best feature may be data flow, which is used to prepare and clean data."
"I've discovered that the new layout of this product makes Docker sharing, machine learning support, and data backups more efficient. Unlike the older method of linking physical, pre-logical, and presentation layers separately, the new interface simplifies this process. Additionally, the integration of databases and machine learning is seamless, with the new visualization approach being particularly beautiful and highly beneficial."
"The solution is user-friendly."
"It plays a crucial role in facilitating decision-making for various organizational stakeholders."
"The product is easily customized."
"The specific capability I find important in Oracle Analytics Cloud is that it allows the basic user to easily drag and drop data. I also like that the solution allows the user to decide what to measure and what to see in the reports."
"Data handling is one of the best features of SAS Visual Analytics."
"I believe that the possibilities for exploring data and formulating visual results are quite good because it allows the business analyst to have different perspectives on the data."
"It provided the capability to visualize a bunch of data in an organized way."
"Great for handling complex data models."
"It integrates well with SAS, making it simple and quick for developers."
"Visual Analytics is very easy to use. I use Visual Analytics for all the typical use cases except text mining. I used it to analyze data and monitor statistics, not text mining. I also use it for data visualization as well as creating interactive dashboards and infographics."
"The product is stable, reliable, and scalable."
"The alert generation feature also helps in sending out ad hoc messages to the business users if business thresholds have been crossed."
"The price of the solution could be lower."
"One area of improvement is associated with more connectors needing to be added such as Microsoft OneDrive, Teradata and a few others. I think the list is limited to the top ones now."
"Its FAW feature has limitations in terms of usage."
"The solution could be more flexible."
"They could improve the ease of developing the dashboard and interacting with it."
"Its machine learning and visualization capabilities can be improved. There should be more visualization options."
"At this time, dataflows cannot be shared, but I think that this should be enhanced."
"The migration of older dash tools from the classic interface of Oracle BI prior to OAS launch to the newer Data Visualization and Oracle Analytics Cloud interfaces, including dashboards and metadata, is currently a cumbersome process. Improvements in this area would be highly beneficial. Additionally, the administration of the cloud, particularly the startup of services and linking of the WebLogic server and integrated components, takes longer than desired. In today's enterprise landscape, waiting forty minutes for the server to be operational is quite lengthy; ideally, this process should take a maximum of four minutes. It would be excellent to incorporate metadata management as an integral part of the Oracle Analytics Cloud. When dealing with integrated data from various sources, tracking data lineage and the entire data life cycle, from sources to report development and the mapping of reports to specific dashboards, should be seamlessly managed within the Oracle Analytics Cloud. This would eliminate the need for additional tools. Drawing a comparison, tools like Tableau have a feature enabling metadata management, making it easier to trace the complete data lineage of reports. Managing over seven hundred and thirty-six business dashboards, the metadata management capability within Tableau simplified the process of understanding how reports were developed, including details like associated tables, users, linked views, materialized views, data segmentations, ETL jobs, and the data warehouse stages. Enhancing metadata tracking within the Oracle Analytics Cloud layout would facilitate easy and practical management of the complete data life cycle, encompassing user accessibility and report permissions."
"The solution should improve its graphics."
"Better connectivity with other data origins, better visualization, and the ability to create KPIs directly would all help."
"The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good."
"The solution is a little weak at the front end."
"The installation process can be a bit complex."
"There are scalability issues. It depends on the data volume and number of end-users. VA requires a lot of hardware resources to move volumes of data."
"It is not as mature as competitors such as Tableau and QlikView."
"A bit more flexibility in the temperatization will be helpful."
Oracle Analytics Cloud is ranked 6th in Data Visualization with 24 reviews while SAS Visual Analytics is ranked 8th in Data Visualization with 35 reviews. Oracle Analytics Cloud is rated 8.0, while SAS Visual Analytics is rated 8.0. The top reviewer of Oracle Analytics Cloud writes "Reliable, capable of handling massive amounts of data, and good value for money". On the other hand, the top reviewer of SAS Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". Oracle Analytics Cloud is most compared with Databricks, Oracle OBIEE, Tableau and Microsoft Power BI, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Databricks, Microsoft Azure Machine Learning Studio and Dataiku. See our Oracle Analytics Cloud vs. SAS Visual Analytics report.
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