Conceptual data modeling is the first step in the top-down approach, where the goal is to capture a satellite view of the business requirements of an organization. As has been claimed by many authors, the main reason for conceptual data modeling is to capture the big picture and comprehend the scope of the high-level requirements of an organization's project. It is worth noting that CDMs are created as a precursor to an LDM or as an alternative to it. 

Conceptual data modeling tries to answer the following questions:

• What problems are involved with the business and require immediate solutions? 
• What are the core concepts of these problems?
• How are these problems related to one another?
• Is there any scope of the effort? What is the scope in relation to the effort made?

The conceptual data modeling process results in a CDM. The model that is created illustrates the key concepts required for a particular application's development. In addition, the model provides a brief overview of the effort required by the company to construct the software:

The preceding diagram shows a conceptual model for a supermarket that wants to measure its sales. As shown in the model, the supermarket intends to keep store dimension, product dimension, and time dimension to generate sales facts. The preceding diagram clearly illustrates that the company wants to measure the sales per product, per dimension, and per date. Conceptual data modeling helps to determine the scope and direction of the application under consideration. In addition, it helps to create a preliminary analysis and definitions of key terms. The conceptual model comprises the most important concepts of the project and requirements that each of those concepts can be defined, and documented. To summarize, the CDM explores the topmost relationships between several entities. Hence, this type of model can be referred to as a domain model.