Model Data

Bridge the gap between your data and our analytics.

In this section you will learn how to create a data model for your data source, which is then used to analyze your data. In GoodData, the data model is broken down into the Physical Data Model (PDM) and Logical Data Model (LDM).

Model Data Section Overview

Before you create your data model, it’s worth asking yourself what business questions you want answered using GoodData analytics. That should be your guiding principle for designing a robust logical data model that will remain in use for years to come.

The Logical Data Model in GoodData

Data modeling in GoodData revolves around the concept of an LDM. You create and modify the LDM for a particular workspace using our fully integrated LDM Modeler. See Logical Data Model in GoodData - Introduction to learn why the LDM is so valuable.

The LDM represents relationships between data objects in a workspace. The LDM provides a layer of abstraction so that you do not have to interact directly with the relational model of your database using SQL. The relational model is represented by a physical data model (PDM).

In the LDM Modeler, you assemble:

GoodData is designed to enable you to quickly create and modify LDMs and publish them to workspaces. However, be careful with how you assemble the components of your LDM. Whenever possible, deploy experienced modelers to your workspaces, particularly if they involve multiple interacting datasets or specialized use cases for your data.

If you are new to BI data modeling, invest time and effort to study data modeling practices prior to implementing a production GoodData solution. Read the following articles to learn more about how to create a good LDM:

If you use a workspace hierarchy, the LDM is inherited and distributed to child workspaces from a parent workspace.