Tool Information
Sisense is an AI-powered analytics platform built to embed intelligence into various products. It offers tools for pro-code, low-code, and no-code capabilities, making it applicable to a range of users from developers to end-users. With Sisense, users can seamlessly create analytical experiences, manage analytics through the release processes, and easily access data from multiple sources. The platform also features conversational analytics capability, which enriches user experience with analytics chatbots, narratives, and AI features. Advanced users have access to a RESTful web API, and developers can run standard SQL queries to get data from data models. One key feature of Sisense is its actionable intelligence capability enabling users to take direct actions based on data-driven insights. It provides explainability, allowing users to assess data outcomes and interpret analytics. Sisense is scalable, simplifying the developing and managing of analytics, and offers the ability to join multiple data sources and create relationships for extensive data modelling. With its single sign-on feature, Sisense further improves user experience by streamlining the authentication process. The platform caters to several industries, including healthcare, retail, manufacturing, tech, financial services, and pharma and life sciences, helping businesses achieve their goals through data-driven decisions.
F.A.Q (20)
Yes, Sisense supports both pro-code and no-code capabilities, providing a flexible platform for users of varying technical capabilities.
Sisense can be utilized by a broad range of users, from developers to end-users. This includes individuals who are comfortable with pro-code, those who prefer low-code environment, and users who favor no-code capabilities.
Sisense enables users to create analytical experiences in a seamless manner. It provides the tools needed for embedding analytics within various products, enhancing the value these products deliver. Furthermore, users can leverage RESTful web API and SQL queries to extract data from multiple sources, enabling comprehensive analysis.
Yes, Sisense can manage analytics through various release processes. This is possible thanks to its Git Integration functionality that allows managing analytics seamlessly through development to release stages.
Sisense is capable of accessing data from multiple sources. This capability allows users to retrieve, analyze and interpret data, further strengthening their analytics and decision-making abilities.
Sisense's conversational analytics capability enriches the user experience with analytics chatbots, narratives, and additional AI features. This provides an interactive way for users to engage with data and achieve meaningful insights.
Yes, Sisense provides AI features such as analytics chatbots and narratives. These features enhance user interaction with data, providing a more immersive analytical experience.
Advanced users and developers have access to the RESTful web API in Sisense. This provides enhanced server functionalities and allows users to interact with data more comprehensively.
Users can run standard SQL queries in Sisense to get data from their data models. This allows for in-depth data exploration and manipulation, leading to more insightful analytics.
Sisense's actionable intelligence capability enables users to take direct actions based on data-driven insights. This means that insights generated by the system can prompt actions, enhancing efficiency and effectiveness of decisions.
The explainability feature of Sisense allows users to quickly assess data outcomes and interpret analytics. It improves understanding of results, ensuring that users can make informed, data-driven decisions.
Sisense can join multiple data sources and create relationships for extensive data modeling. This allows users to create comprehensive and insightful visualizations and analyses in a streamlined manner.
Yes, Sisense offers a single sign-on feature. This improves the user experience by streamlining the authentication process.
Sisense can be applied in several industries, including but not limited to healthcare, retail, manufacturing, tech, financial services, and pharma and life sciences.
Yes, Sisense has applications in both the tech and financial services industries. The platform enables businesses in these sectors to gain meaningful insights from their data, assisting them in reaching their goals through data-driven decisions.
Sisense aids in making data-driven decisions by providing tools for comprehensive analytics. Its actionable intelligence capability enables users to take direct actions based on insights, facilitating effective decision-making.
Yes, Sisense is appropriate for embedding intelligence into product development. It offers capabilities across pro-code, low-code, and no-code, making it suitable for a range of development processes.
FusionCompose SDK is a new release from Sisense that gives users full control over their analytics experience within the product. It facilitates the creation of seamless analytics experiences in any product.
Yes, with Sisense's Javascript API & Add-ons, users can build new widgets, tweak out-of-the-box visualizations, and apply custom formatting. These capabilities allow users to customize their analytical interface to suit their needs and preferences.
Sisense Single Sign-On authenticates users by confirming their credentials, then signaling to Sisense that the user has been authenticated. This simplifies access for the user, enhancing the overall user experience.
Pros and Cons
Pros
- Pro-code
- low-code
- no-code capabilities
- Seamless analytical experiences
- Scalability for analytics management
- Multi-source data access
- Conversational analytics feature
- RESTful web API for developers
- Actionable intelligence capability
- Data interpretability (Explainability)
- Data modelling across multiple sources
- Single sign-on feature
- Industry-specific applicability
- Git Integration
- Standard SQL queries for data extraction
- User and developer authentication
- Developer-friendly with API and SDKs
- Embeddable intelligent analytics
- Javascript API for custom widgets
- Cloud and on-premise deployment
- Connectivity for quick data access
- Comprehensive data visualization
- Extensive data modeling capability
- Robust security and authentication
- API and SDK compatibility
- Supports multiple data connectors
- Scalability and flexibility
- Interactive data exploration options
- Enables actionable insights
- Data storytelling for decision making
- Supports various industries & departments
- Git integration for developers
- Analytic chatbots and narratives
- Workflows for release processes
- Cloud-native for fast performance
- Data outcomes for analytics interpretation
- Developer Portal and Playground
Cons
- No-code usability not specified
- SQL needed for data extraction
- Complex for basic users
- Limited explainability features
- Dependent on data quality
- No obvious real-time capabilities
- Limited predictive analytics
- Learning curve for SDK
- Industry-specific features not specified
- Limited tools for data cleaning
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