Create a Logical Data Model from Your Cloud Data Warehouse

This tutorial guides you through the process of creating a logical data model (LDM) in your workspace using tables and views in your data warehouse (for example, Snowflake or Redshift). A newly created workspace does not have an LDM therefore you are going to create an LDM from scratch.

You create an LDM in the LDM Modeler. To do so, perform the following steps:

  1. Create a Data Source.
  2. Connect the Data Source to the LDM Modeler.
  3. Add datasets.
  4. Publish the LDM.

Create a Data Source

Create a Data Source for the data warehouse that holds the files with data that you want to upload to your workspaces. For more information, see Create a Data Source.

During data load, the GoodData platform connects to the data warehouse using the information from the Data Source, downloads the data, and uploads it to the workspaces according to how the datasets in the LDM are mapped to the files.

Connect the Data Source to the LDM Modeler


  1. On the top navigation bar, select Data. The LDM Modeler opens. You see a blank canvas area in view mode.

  2. Click Edit. The LDM Modeler is switched to edit mode.

  3. In the left panel, open the list of available Data Sources, select the Data Source that you created at the previous step, and click Connect

     The Data Source is connected to the LDM Modeler, and the tables and views from the data warehouse are listed in the left panel.

    You are now going to add datasets based on those tables and views.

Add Datasets

You are now going to create datasets by importing the tables and views from the connected data warehouse to the LDM Modeler.

When a table/view is being imported, the LDM Modeler tries to auto-detect the types of the data in the table/view. The data can be detected as one of the following:

  • Fact, a numerical piece of data, which in a business environment is used to measure a business process (see Facts in Logical Data Models)
  • Attribute, data that is to be used in grouping or segmenting the values resulting from the computed functions (see Attributes in Logical Data Models)
  • Primary key, an attribute that serves as a unique identifier for a row of data in a table and as a connection point that allows you to connect this dataset to another dataset (see Connection Points in Logical Data Models)
  • Reference, a connection point (foreign key) from another dataset (see Connection Points in Logical Data Models)
  • Date, data representing dates Dates are managed through a separate object, the Date dataset (see Dates in Logical Data Models). If you are importing a table/view that contains dates, not one but two datasets will be added to your LDM: one Date dataset for the dates, and the other one with the rest of information from the table/view. These two datasets will be automatically connected with a relationship, and the Date dataset will become a reference in that other dataset.


  1. To add a dataset, drag a table/view from the left panel and drop it in the blank canvas area. The data preview opens. The preview shows the data from the table/view and looks similar to the following: 

      Based on the column names and the contents of those columns in the table/view, the column names and the types of the data are suggested for the dataset that will be created from this table/view.

  2. Review the suggested column names and the data types. Update them if needed. For more information about the data types and how to set them correctly, see Create a Logical Data Model from CSV Files.

  3. Once done, click Import. The table/view is imported, and the dataset is added to the LDM Modeler. Every column in this dataset is mapped to the appropriate column in the table/view in your data warehouse. During data load, the data from a column in the table/view will be loaded to the corresponding fact or attribute in the dataset. For more information about the mapping, see Mapping between a Logical Data Model and the Data Source.

  4. Repeat Steps 1-3 to add more datasets.

  5. Update the LDM if needed. For example, you may add or delete relationships between datasets, modify attributes or facts in the datasets, and so on. For more information, see Update a Logical Data Model.

Your LDM is ready. You can now publish it.

Publish the LDM

To publish the LDM, follow the instructions from Publish a Logical Data Model.