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Sisense’s Q3 product release focuses on our Live Data models, which power Sisense dashboards to run queries in real-time from cloud data warehouses. Live Data models enable users to analyze their data with no latency, leaving the data ‘as-is, where-is.’ Our latest release, which includes Live Data model updates such as custom columns and pre-defined drill hierarchies, as well as a new native connector for Azure Synapse, strengthens Sisense’s commitment to working with CDW data and is aimed at enhancing the data modeling experience.
Additionally, Sisense continues to extend its AI and natural language query capabilities, with Embedded NLQ, providing embedded analytics customers the ability to gain deeper and faster insights without leaving the context of their workflows, as well as several NLQ enhancements for our self-service analytics customers.
Data from anywhere to run everywhere
Live Data models power Sisense dashboards with data and updates coming directly from external databases, without the need to import data into ElastiCubes. Sisense’s web-based visual semantic layer is used to manage the schema and connections to data tables across databases, giving users the ability to tap into the benefits of high performance database technologies and leverage their existing data infrastructures. In Q3, we’ve released several enhancements for Live Data models.
Simplify complex data and gain greater agility in data transformations by adding new custom columns to existing tables. This is useful when combining data from different existing columns, and when needing to cleanse and prepare data. The new columns provide dashboard designers with additional fields to use as is, or as a basis for more advanced calculations in widgets. Use SQL to customize the values contained within the custom columns.
With Sisense’s “drill-to-anywhere” feature, viewers can select a drill-down path from a complete list of fields, but it’s often easier to select a frequently-used drill hierarchy from a short list. This is especially true when there is a lot of data, and the Viewer needs to remember specific fields, and select them each time.
Leverage data from Azure Synapse, Microsoft’s new limitless analytics service, within Sisense. Azure Synapse brings together enterprise data warehousing and Big Data analytics, giving users the freedom to query data on their terms, using either serverless or provisioned resources—at scale. With Sisense’s native data connector, users bring these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and analytics. Available for both Live and ElastiCube models.
Create data models faster and with higher quality by eliminating manual data prep steps using AI. Group Similar automatically resolves discrepancies in the data to create a cleaner experience for data analysts and end-users, such as grouping values for America, USA, US, United States into a single value. Previously available on Windows, Group Similar is now also available for Linux.
Save the step of preparing a temporary machine to install Linux deployments. Instead of downloading several packages and preparing the environment, data administrators can leverage Sisense’s Docker container, in which all necessary packages and setup environment come pre-installed.
Data exploration for every skill set
Embed Sisense NLQ directly into any application to enable non-technical users access deeper insights, faster without leaving the context of their workflows. Assisted by the Sisense AI engine, Sisense Embedded NLQ will make Sisense NLQ UI components (“Simply Ask”) accessible for embedding via Embed SDK or Sisense.JS. With automated NLQ data model generation and specialized machine-learning/NLQ algorithms, product teams can delight their customers through innovative analytic workflows and rapid time to deeper insights.
Read more about Embedded NLQ
Sisense NLQ (Natural Language Query), which was released earlier this year, enables users to ask sophisticated questions in an easy way with natural language. Since the initial release, Sisense has continued to enhance its NLQ offering with several additional capabilities. Now available for Live Models, Sisense NLQ also supports forecast and trends models, meaning that users can ask predictive questions such as “What will our weekly revenues be 10 weeks from now?” or “How will our operating costs increase over the next three quarters?” in natural language.
Gain advanced, predictive forecasting for all users within a menu-driven, point and click interface. Sisense Forecast uses ensembles of advanced forecasting models that come out of the box. No data science, R or Python expertise is required. Previously available for Windows, Sisense Forecast is now also available in Linux.
Flexible, customizable enterprise-grade analytics
Control who can view or create dashboards for specific models/cubes, allowing granular access control per model. There are now three types of permissions, users who can edit models, users who can create and view dashboards, and users who can only view dashboards. Granular data model access will be of special relevance for finance and HR departments, as well as for embedded use cases of Sisense. Specific dashboards can be exposed to end-users without necessarily granting them design permissions on the full models the dashboards were created on. Embedded analytics clients can now grant their customers the ability to create their own models and dashboards, while limiting their ability to create additional dashboards on the predefined Elasticubes and dashboards shared with them.
Build data experiences and analytic apps your users will love.