Creating a Data Model in CloudConnect (Summary)
CloudConnect is a legacy tool and will be discontinued. We recommend that to prepare your data you use the GoodData data pipeline as described in Data Preparation and Distribution. For data modeling, see Data Modeling in GoodData to learn how to work with Logical Data Modeler.
The logical data model for the sample Human Resources application is now complete. In the process, you have learned the logical data model objects for creating:
- Datasets (Attributes and Facts)
- Date dataset
- Relations
These components are the core objects used in creating your logical data models in CloudConnect.
To implement the rest of the application, complete the following steps:
- Generate source data for the application. You can use the source data at the beginning of this tutorial as the basis for creating your CSV file.
- Publish the data model to the GoodData project. For more information on publishing, see Publishing Logical Data Models in CloudConnect.
- Create the ETL graph in CloudConnect to extract, transform, and load the source data into your GoodData project. See Loading Data Using CloudConnect. At this point, you have created the mechanisms for taking the source data, transforming it, and loading into the platform for storage based on the logical data model that you have built.
- Build the GoodData metrics, reports, and dashboards to utilize the data through the data model.
- If you are planning to use this data model across multiple projects, clone your CloudConnect project, export it, and then import into each destination project.