Common data model
Imagine you have many different toys, all with their own shapes, colors, sizes, and functions. As you play, you may want to sort them or put them together to create different games and stories. However, if each toy speaks a different language or has different rules, it may be hard to do so.
Similarly, in the world of computers and data, there are many different systems, applications, and devices that collect, store, and analyze information. For example, your doctor may have records of your medical history in one software, while your school may have records of your grades and attendance in another. These systems were created to fulfill specific purposes, and they may use different formats, structures, and terms to describe the same information.
Here is where the common data model (CDM) comes in. It is like a toy box that can organize and standardize the data from different sources, so that it is easier to use and share. The CDM includes predefined sets of entities (like toys), attributes (like shape or color), and relationships (like which toys belong to the same game) that reflect common concepts and practices across industries and applications (like healthcare, finance, or education).
For instance, one entity in the CDM may be 'person', which includes attributes such as 'name', 'birthdate', and 'gender'. Another entity may be 'appointment', which includes attributes such as 'date', 'time', and 'provider'. By using the same entities and attributes across different software, it becomes simpler to compare, aggregate, or enrich the data.
Moreover, the CDM can also enable interoperability, which means that different systems can exchange and use data from each other seamlessly. For example, a hospital may use its own electronic health record (EHR) system to track patients' health information, while a research study may use a separate data management system to collect and analyze data from multiple sources. If both systems adhere to the CDM, they can easily share patient-related data without requiring extensive data transformation or mapping.
Overall, the common data model is like a language that lets computers and humans communicate more effectively and efficiently. It can reduce redundancies, errors, and costs associated with managing disparate data sources, and enable more advanced analytics and insights.
Similarly, in the world of computers and data, there are many different systems, applications, and devices that collect, store, and analyze information. For example, your doctor may have records of your medical history in one software, while your school may have records of your grades and attendance in another. These systems were created to fulfill specific purposes, and they may use different formats, structures, and terms to describe the same information.
Here is where the common data model (CDM) comes in. It is like a toy box that can organize and standardize the data from different sources, so that it is easier to use and share. The CDM includes predefined sets of entities (like toys), attributes (like shape or color), and relationships (like which toys belong to the same game) that reflect common concepts and practices across industries and applications (like healthcare, finance, or education).
For instance, one entity in the CDM may be 'person', which includes attributes such as 'name', 'birthdate', and 'gender'. Another entity may be 'appointment', which includes attributes such as 'date', 'time', and 'provider'. By using the same entities and attributes across different software, it becomes simpler to compare, aggregate, or enrich the data.
Moreover, the CDM can also enable interoperability, which means that different systems can exchange and use data from each other seamlessly. For example, a hospital may use its own electronic health record (EHR) system to track patients' health information, while a research study may use a separate data management system to collect and analyze data from multiple sources. If both systems adhere to the CDM, they can easily share patient-related data without requiring extensive data transformation or mapping.
Overall, the common data model is like a language that lets computers and humans communicate more effectively and efficiently. It can reduce redundancies, errors, and costs associated with managing disparate data sources, and enable more advanced analytics and insights.
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