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Summary

Data Architecture & Engineering Services
A Quick Guide to Data Dictionary
What is a Data Dictionary?
A data dictionary 1 is a collection of descriptions of data objects or terms, definitions, and properties in a
data asset. Data dictionaries provide information about the data

Data dictionaries are an essential communications tool for data modeling, curation, governance, and
analytics, especially when dealing with datasets that have been collected, compiled, categorized, used, and
reused by different internal and external data Consumers across the organization

Why do you need a data dictionary?
Data dictionaries provide valuable definitions for the data as well as help data Consumers understand any
data asset before delving into the details within that asset. In order for data to be trusted and appropriately
used, it must be understood and supported by clear definitions

An established data dictionary can provide organizations many benefits, including:
• Greater data standardization and consistency across the organization or domain
• Improved analysis and decision-making based on better understanding of data
• Improved documentation
• Increased reuse of data
What is in a Data Dictionary?
A data dictionary consists of several data components, which contains multiple levels: data asset, entity,
attribute, and value domain. Each level includes different components, but each component should be
defined with the following properties:
Data Component Name Data Component Name that represents a class of real-world entities or characteristics
of those entities
Description A short description for the data component name
Type Logical or physical data component
Required Required or optional data component
Sample A sample of the data component
The data asset level is composed of one line that contains a data asset profile, which includes the data asset
name, description, type, version, and create and last update date

1
Refer to the CMS Data Description Guidelines webpage to download the Data Dictionary Template

Last Updated: 03/30/2021 OIT|EADG|DEA|DAES 1
A Quick Guide to Data Dictionary
The entity level is composed of one line per entity/table that contains all required properties for this
element, such as logical and physical data element name, requirement ID (justification for having this entity
in the system), security category (Consumers that can access this entity) and so forth

The attribute level is composed of one line per attribute/column that includes logical and physical data
element name (as well as parent element, i.e. entity/table name) and some logical and physical properties
(data type and size, null option, is attribute/column a primary key, a foreign key, an unique/alternative key,
PII field, etc.)

Finally, the value domain level is composed of a list of groups/collections of similar values (sex codes,
account types, credit card types, enrollment plans, etc.) defined as business rules, look-up tables or list of
valid values, and each available value within each collection

Logical vs. Physical Data Dictionary
A logical data dictionary describes information in business terms and focuses on the meaning of terms and
their relationship with other terms. A physical data dictionary represents data in a specific database and
includes actual tables and columns in the data asset’s schema

• Logical: Business-related names, entities/attributes, logical naming convention (mixed case)

• Physical: Technical names, tables/fields, platform-driven naming convention, field length and data
types. Platform-specific

How do you create and maintain a Data Dictionary?
Most data modeling tools and database management systems (DBMS) have built-in, active data dictionaries
the capable of generating and maintaining data dictionaries. Data stewards may also utilize the CMS Data
Dictionary Template 2 and guide for manually creating a simple data dictionary in Excel

Best Practices:
• Start building a data dictionary during the gathering business requirements phase

• The data dictionary is a living document that must be regularly maintained

• If utilizing erwin, then Consumers should build the data dictionary from their data model using
Report Designer

• Reference the CMS Data Naming Quick Reference Guide 3 for data naming guidance

• Reference the CMS Data Definition Quick Reference Guide 4 for data definition guidance

2
Refer to the CMS Data Description Guidelines webpage to download the Data Dictionary Template

3
For additional data naming guidance, refer to the CMS Data Naming Quick Reference Guide

4
For additional data definition guidance, refer to the CMS Data Definition Quick Reference Guide

Last Updated: 03/30/2021 OIT|EADG|DEA|DAES 2

A Quick Guide to Data Dictionary What is a Data Dictionary? A data dictionary 1. is a collection of descriptions of data objects or terms, definitions, and properties in a data asset. Data dictionaries provide information about the data. Data dictionaries are an essential communications tool for data modeling, curation, governance, and