Why Data Definition is EssentialĪs mentioned above, and in our overview of data modeling, database tables without definitions are often counterintuitive (at best). Keeping the data dictionary within the data warehouse or near the raw data is an optimal arrangement, with the perfect data dictionary being one that furnishes a high-level description of every single field in your data as well as the ability to learn more as needed. In other words, while running a query, ends users shouldn’t also be required to go on a hunting expedition for definitions.
When implementing a data dictionary, it’s ideal to house it as close to the data set as possible, providing added ease of accessibility. Each data field has an important role to play clearly defining that role is one of the most pragmatic steps an organization can adopt into their data program. Yet, of all things data related, it is often the entity that receives the least amount of attention, sometimes left as a last step in a data program or not implemented at all.Ī data dictionary labels and describes how an organization collects, transforms, and stores its (data) inventory without one, data may seem vague or mysterious as end users observe data without comprehending it. It’s a tool that simultaneously requires a low-level amount of work while yielding a high-level amount of value. When data is collected and stored, properly defining each field’s meaning and purpose is the job of a comprehensive data dictionary. Practical Data Dictionary Design and Maintenance What Is a Data Dictionary
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