Webcast : ER/Studio Business Architect

A conceptual data model is a high-level representation of the data of an organization that focuses on the dominant entities, their relationships, and key attributes, without going into the details of specific data types, formats, or storage. It provides an abstract display of the data landscape, allowing stakeholders to understand the overall structure of the data and how it relates to the processes and objectives of an organization.

The conceptual data model is important for data strategy for several reasons:

• Communication: It serves as a common language for stakeholders, including business users, analysts, architects, and developers, to discuss and understand the data requirements of an organization.
• Alignment: It helps align the data strategy with the goals and objectives of an organization, ensuring that data initiatives support business needs.
• Identification of key entities and relationships: It highlights the main data entities and their relationships, providing a basis for designing more detailed data models, such as logical and physical data models.
• Data governance: It supports data governance efforts by providing a high-level understanding of the data landscape of an organization, which we can use to establish data policies, standards, and processes.
• Flexibility: It allows for easier adaptation to changes in business requirements, as it is less intent on implementation details and more on the overall structure and relationships of the data.

Explore how to position your conceptual data model and acquire techniques for engaging stakeholders and avoiding pitfalls. Starting from the importance of “precision”applied to conceptual data models, Steve Hoberman walks us through the challenges, the connection to data strategy and key takeaways from the projects he managed.

Witness the power of the conceptual data model and see how it can help you with your data strategy.

Steve Hoberman shares his over 30 years experience on conceptual data models to help you with your data strategy. Steve has trained over 10,000 people in data modeling since 1992 and he’s the author of nine books on data modeling.