The Semantic Layer is where you create area-specific data models and push them out to your desired front-end tool. Enabling easy, self-service access to relevant data across multiple platforms.

The modeling capabilities in the Semantic Layer provide department or purpose-specific models of your data using terms and definitions that business users understand. This allows for fast creation and flexible modification of dashboards and reports. Because a single model is created once, then deployed to multiple front end solutions, users get the same fields and figures regardless if they are using Power BI, Tableau, or Qlik.

TimeXtender's approach to the Semantic Layer allows users to create or modify a Semantic model only once, however, this change can be deployed to any, or all, of the following endpoints simultaneously. Meaning that while the organization may be using multiple visualization tools, this does not need to increase the amount of work required to build or modify a model. This approach also drastically improves data governance, ensuring all users are consuming a single version of truth, regardless of the tool they use.

SQL Server Analysis Service Tabular, which uses the same in-memory analytics engine as Power BI, making it the ideal location for data models when using Power BI as your front end solution.

The Tableau Endpoint generates a Tableau Data Source (.tds) file. This file includes all the necessary fields and relations enabling users to immediately begin developing powerful dashboards in Tableau Desktop, or upload the data source to Tableau Server or Tableau Online.

Qlik models can be deployed directly to QlikView, QlikSense Desktop or QlikSense Server. Complete with all the scripts necessary to generate QVDs and create a complete data model, Qlik users can easily create dashboards on complex data without having to write any Qlik script.