Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Knime and others in Data Science Platforms.
The product offers a significant return on investment through its scalability and integration capabilities.
My customers have seen returns on investment through increased efficiency, automated calculations, improved accuracy in pricing, and reduced staffing needs due to the automation.
The enterprise subscription offers more benefits, ensuring valuable outcomes.
The community access is weak, which limits the ability to engage in discussions and find documentation and examples of similar cases effectively.
The support quality depends on the SLA or the contract terms.
They provide callbacks to ensure clarity and resolution of any queries.
Watson Studio is very scalable.
I rate IBM Watson Studio seven out of ten for scalability because while it scales, it requires significant resources to do so, making it expensive compared to some competitors.
Expertise in optimization is necessary to manage such issues effectively.
SAS Visual Analytics is stable and manages data effectively without crashing.
IBM should work on optimizing the user interface and enhancing the product's accessibility for medium and small enterprises.
One area that could be improved is the backup and restoration of the database and the overall database configuration.
In terms of configuration, I would like to see AI capabilities since many applications are now integrating AI.
IBM Watson Studio is considered rather expensive, with a rating of six or seven.
This capability saves a significant amount of time by automating processes that typically involve manual work, such as data cleaning, feature engineering, and predictive analytics.
It integrates well with other platforms and offers good scalability.
The ability to query information from our Excel data into SAS to view specific data is invaluable.
IBM Watson Studio provides tools for data scientists, application developers and subject matter experts to collaboratively and easily work with data to build and train models at scale. It gives you the flexibility to build models where your data resides and deploy anywhere in a hybrid environment so you can operationalize data science faster.
SAS Visual Analytics is a data visualization tool that is used for reporting, data exploration, and analytics. The solution enables users - even those without advanced analytical skills - to understand and examine patterns, trends, and relationships in data. SAS Visual Analytics makes it easy to create and share reports and dashboards that monitor business performance. By using the solution, users can handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. SAS Visual Analytics is most suitable for larger companies with complex needs.
SAS Visual Analytics Features
SAS Visual Analytics has many valuable key features. Some of the most useful ones include:
SAS Visual Analytics Benefits
There are many benefits to implementing SAS Visual Analytics. Some of the biggest advantages the solution offers include:
Reviews from Real Users
Below are some reviews and helpful feedback written by PeerSpot users currently using the SAS Visual Analytics solution.
A Senior Manager at a consultancy says, “The solution is very stable. The scalability is good. The usability is quite good. It's quite easy to learn and to progress with SAS from an end-user perspective.
PeerSpot user Robert H., Co-owner at Hecht und Heck GmbH, comments, “What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes.
Andrea D., Chief Technical Officer at Value Partners, explains, “The best feature is that SAS is not a single BI tool. Rather, it is part of an ecosystem of tools, such as tools that help a user to develop artificial intelligence, algorithms, and so on. SAS is an ecosystem. It's an ecosystem of products. We've found the product to be stable and reliable. The scalability is good.”
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