kdb Insights brings the small but mighty kdb engine to data scientists and engineers with full support for Docker and Kubernetes and native integration with industry-standard programming languages. It’s the fastest time series analytics engine!
Fully cloud-enabled to operate on AWS, Azure, and GCP as well as on-prem private-cloud environments, kdb Insights allows you to harness the technology that powers Wall Street directly within your cloud services. It lets you modernize your cloud-native analytics stacks and develop transformative machine learning operations (MLOps) pipelines.
With kdb Insights Enterprise Edition – the fastest and most efficient time series analytics engine in the cloud – you can harness the technology that powers Wall Street. With its integrated data management and streaming analytics engine, kdb Insights Enterprise makes it easier for data scientists and analysts to create robust, production-ready data-driven applications. Using an easy-to-use interface, data scientists and business users can work alongside expert coders to design real-time pipelines and dashboards and deploy them into resilient, high-availability, and autoscaling infrastructures.
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:
- Data
- Interactive data discovery
- Augmented analytics
- Chat-enabled analytics
- Sharing and collaboration
- Visual analytics apps
- Embedded insights
- Location analytics
- Security and administration
- In-memory engine
SAS Visual Analytics Benefits
There are many benefits to implementing SAS Visual Analytics. Some of the biggest advantages the solution offers include:
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Machine learning and natural language: SAS Visual Analytics uses machine learning and natural language explanations to find, visualize, and narrate stories and insights that are easy to understand and explain. This enables you to find out why something happened, examine all options, and uncover opportunities hidden deep in your data.
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Easy and efficient reporting: With SAS Visual Analytics, you can create interactive reports and dashboards so you can quickly summarize key performance metrics and share them via the web and mobile devices.
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Easy to use: SAS Visual Analytics was designed to be easy to use. Its easy-to-use predictive analytics enables even business analysts to assess possible outcomes, which also helps organizations make smarter, data-driven decisions.
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Self-service data: Self-service data preparation gives users the ability to import their own data, join tables, create calculated columns, apply data quality functions, and more. In turn, the solution empowers users to access, combine, clean, and prepare their own data in an agile way, which helps facilitate faster, broader adoption of analytics for your entire organization.
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.”