Data Dictionary Defined
A data dictionary provides a descriptive list of names, definitions, and attributes of data elements to be captured in an information system or database. It describes the definitions or the expected meaning and acceptable representation of data for use within a defined context of data elements within a data set. It also provides metadata or information about data.
The metadata may include other attributes or characteristics such as length of data element, data type (e.g., alphanumeric, numeric, date, special symbols), data frequency (mandatory or not), allowable values or constraints, originating source system, data owner, data entry date, and when the data element is no longer collected. The goal is to achieve consistently defined and standardized data.
Common Data Inconsistencies
In many organizations data are stored in different databases and may be of inconsistent quality. Issues such as variable naming conventions, definitions, field length, and element values can all lead to misuse or misinterpretation of data in reporting. The following examples illustrate common data inconsistencies.
Data dictionaries should be accessible to data analysts and those authorized users in the organization or enterprise who manage data, use data to manage their work, contribute data to other internal or external systems, and external audit organizations conducting assessments of information system capabilities. The ability to edit the dictionaries, however, should be limited to system administrators.
A data dictionary can be consulted to understand a data element’s meaning and provenance. It is a dynamic document that must be updated as data collection requirements change. The dictionary acts as a resource when reviewing results of reports generated from a data system. It serves as an important tool during data sharing, exchange, or integration purposes.
While data dictionaries are useful for the consistent collection of data, it is imperative that the data are managed and validated for accuracy in reporting.
Why Data Standards Matter
Data standards are an integral component to an organization’s data dictionary. Organizations should align the entries in their data dictionary with current data standards to ensure they are incompliance.
Standards play an important role in organization. Standards also have enhanced organizational leaders’ ability to interpret their data for customer care, business, research, and comparative performance improvement reporting activities.
The Benefits of a Data Dictionary
A data dictionary promotes data integrity by supporting the adoption and use of consistent data elements and terminology within health IT systems. By adopting a data dictionary, organizations can improve the reliability, dependability, and trustworthiness of data use.
An established data dictionary can provide organizations and enterprises many benefits, including:
- Improved data quality
- Improved trust in data integrity
- Improved documentation and control
- Reduced data redundancy
- Reuse of data
- Consistency in data use
- Easier data analysis
- Improved decision making based on better data
- Simpler programming
- Enforcement of standards
A data dictionary promotes clearer understanding of data elements; helps users find information; promotes more efficient use and reuse of information; and promotes better data management.