Helping You Get the Most Out of Dundas BI February 2018
Connecting to Data via REST Services
As many web-based data sources expose data through a REST API, many organizations need to integrate this data into their existing data analytics solutions in order to provide a fully automated access to all of their data. The challenge here is that there are many variations in the way the REST API is implemented for different data sources. To combat that, Dundas BI provides a few ways to complete this task and let you progress to analyzing the data: By creating your own custom data connection or by creating a connection from within your data models using Python or R, you get the flexibility to leverage existing public libraries and samples and connect while also manipulating your data as needed.
Defining a Custom User Experience for Guided Analytics
While adoption for ad-hoc self-service analytics increases as it becomes easier, the majority of data consumers still need Guided Analytics whereby content and interactions are laid out in a pre-defined fashion. Out-of-the-box, Dundas BI provides many built-in interactions to support the users data exploration when starting from scratch or from a pre-defined data view. This enables users to ask the next question or better collaborate with others. When creating a custom guided analytics data view, the content creator often wants to dictate which interactions are available and how the consumer will use those. Doing so can Simplify the UX and drive even higher adoption rates.