Models of Data Architecture
Data architecture typically includes three types of data models:
- Conceptual Data Models (CDM): It gives a broad overview of what should be included in the database. It is usually generated early in the project’s life cycle and is less technical. It enables stakeholders to understand and speak about the data requirements without delving into technical intricacies by giving high-level overview of the business concepts and their relationships.
- Logical Data Models (LDM): Provides a thorough representation of the data pieces and their interactions while being independent of any specific database management system or technology. It specifies entities, characteristics, and relationships but excludes implementation specifics such as primary keys and indexes. It’s more detailed than the conceptual model and provides a blueprint for database design.
- Physical Data Models (PDM): Determines how data will be stored, accessed, and implemented in a given database management system. It describes tables, columns, data types, indexes, keys, constraints, and so on. It is strongly related to the technology employed (for example, a relational database management system such as MySQL or Oracle).
These models are created iteratively, with each iteration improving and adding information to the preceding one. They assist in understanding, creating, and deploying databases that satisfy business requirements successfully.
What is Data Architecture?
Data architecture is the body of rules that defines within the firm how data is gathered, kept, managed, and utilized. The data architecture is the toolset, policies, and standards that help in managing the handling of data assets properly. Data is a vital asset in this respect so it can drive decision-making and also make data available and useful.
In this article, we will understand and explore the meaning, types, frameworks and delve into the depth of What is Data Architecture?
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