Why Do I Need a Data Dictionary?

Why Do I Need a Data Dictionary?

Jul 9, 2018
  • Author:
    Lisa Rothmuller, CPCS
    AVP, Clinical Solutions and CVO Services
    Lisa works with clients and organizations to provide Strategic Account Management and best practice and solution consulting. Lisa has a bachelor's degree in Economics/Finance from Bentley University in Boston, Massachusetts and currently resides in San Diego.

Advances in applications, technology and industry, provide more usage of automation tools. Impediments to taking advantage of these features occur when the data stored in the application includes multiple variations. Common examples include telephone numbers, email address and address standards.

Common Causes

Lack of a Data Dictionary: A data dictionary is a resource used to define the usage, format, meaning and the relationship a particular piece of data has relevant to the system. These resources are crucial for users who input data and are unsure of the correct method in which to do so.

Unlimited User Rights: When users are unfamiliar with the correct format to enter data or are not properly trained in the correct methods, they will commonly defer to personal preference.

No Universal Policy on Data Entry Formats: Without official guidelines, users will develop a particular method of data entry that is not necessarily transmitted to new users or when there is turnover without training.


An organization wished to use email as a means to send communications to their providers. However, it was found that 3% of email fields within the database were either invalid, there wasn’t an email address, or was an incorrect format.


Miscommunication: Organizations that attempt to use data that is not correct can frequently be met with frustration and miscommunication. For example, when a provider is not contacted with important updates, or the provider has updated their contact information but a duplicate record still contains the outdated information. These situations can cause unnecessary tension between the system and the provider.

Inability to Advance: When it has been identified that key elements used for automation are not standardized the system is not effectively able to move forward with new opportunities. The cleanup can be time consuming.

Best Practice

Clean Data: In order to prevent duplication, multiple entries and eliminate confusion, each entry field is identified, color coded and assigned specific user rights according to an online reference.

Implement Universal Protocol: Set up a standard to which all users must adhere when inputting data into the system. A regular audit or communication between IT or related departments of the system can also insure that all standards are being met.