Sisense has announced the release of new advanced analytic functionalities, representing the first product integration since its acquisition of Periscope Data in May. The integration brings forth Sisense Forecast, Sisense Quest, and three new capabilities for embedded BI. Sisense also unveiled an industry-first In-Warehouse Data Preparation module for self-service in multi-cloud environments. The Sisense platform now includes advanced forecasting features that use machine learning to predict future outcomes from seasonal and nonlinear historical data.
Sisense is a global business analytics software company with offices in New York City, Phoenix, Tokyo, and Tel Aviv. The company’s BI software makes it easy for organizations to reveal business insight from complex data in any size, and from any source. Sisense allows users to combine data and uncover insights in a single interface without scripting, coding or assistance from IT. Their BI and analytics platform is sold as a single-stack solution with a back end for preparing and modeling data. It also features expansive analytical capabilities, and a front-end for dashboarding and visualization.
The Q4 2019 release includes highly actionable out-of-the-box statistical or custom machine learning models as well. The models enable users to gain a deeper understanding of their data. The product also touts numerous tools to create a more complete experience for developers who wish to embed analytics within a host application, with minimal code. A new Periscope Data-powered In-Warehouse Data Prep add-on lets users transform and optimize large data sets directly in a cloud data warehouse so teams can deliver business user self-service.
Sisense Forecast is made up of advanced machine learning forecasting capabilities that can be applied via a simple menu option. Best for complex or nonlinear data, the feature enables users to predict future outcomes from data. Sisense Quest allows you to apply advanced analytic models to widgets. The capability allows both out-of-the-box advanced statistical models and custom machine learning models using any time-series visualization. The new release is rounded out by capabilities designed for product teams, including Embed SDK, new embedded dashboard designer privileges, and Embed Code UI Generator.
Latest posts by Timothy King (see all)
- SAS Teases SAS Viya 4 Cloud Analytics at Virtual User Conference - July 8, 2020
- Tellius Launches Tellius On-Demand with Guided Insights - July 8, 2020
- Sisu Unveils New A/B Testing and Text Analytics Capabilities - July 8, 2020