The Relationships Between Data, Information, and Records

by Erica Rice

Data. Information. Record.

These terms are thrown around a lot in the information management world, and they are often used interchangeably. However, each of these terms has a distinct definition and purpose in the practice of records management. Let’s look at the definitions of each of these—and how they are related—to make sure that you, your colleagues, and your TSLAC analyst are on the same page when it comes to talking about data, information, and records.


ARMA International defines data as “any symbols or characters that represent raw facts or figures and form the basis of information.”1 In other words, data are the building blocks of information. When you arrange data in a meaningful way and assign attributes to it, it becomes information that has additional value beyond the raw data.

For example, the phrase “John Smith” is a piece of data that, without context, has no meaning; it is simply a string of characters. However, if you put the data in context with other logical bits of data, it becomes useful information: “This person’s name is John Smith.”


This leads us straight to ARMA’s definition of “information”: “data that has been given value through analysis, interpretation, or compilation in a meaningful form.”2

Data are the building blocks of information. Likewise, pieces of information are the building blocks of records.


Local government and state agency records managers know that state records are defined as any recorded information created or received by a government in the transaction of public business.3 In other words, records are made up of information, and that recorded information is given context by serving as evidence of a specific business transaction.

For example, the phrase “This person’s name is John Smith” is a piece of information, but it does not serve as evidence of any specific action; it is not a record. However, if John Smith were to fill out a form at the county clerk’s office that included his personal information as well as documentation of his request, that form becomes a record. That county clerk record serves as evidence of the public business transacted, and it is made up of many pieces of information.

The Relationship

Here is a visual interpretation of the relationship between data, information, and records:

Visual illustrations of data, information, and records

The data on their own have no meaning; they are simply unrelated raw facts and figures floating in the blank void.

Information arranged in database rows.

Data is given meaning once it is logically organized into information. In this step, we can see that data has been entered into a database and assigned as various attributes under a primary key (the primary key is a field that identifies each unique database entry—e.g., employee number, item number, etc.) Each numbered row of data is information. We can see that each star entry has a unique value, each chevron entry has one of two possible values, and each heart entry has a unique value. These are symbolic representations, but we could imagine that the first line of the database tells us that Employee #001 is named “John Smith,” he works on the North Campus, and his phone number is 512-555-5555. All these bits of employee data are meaningless on their own, but once they are entered into the correct spot in this structured database, they provide us with valuable information about each employee.

Side Note: Information technology (IT) and records management professionals may run into conflict over their use of the term “record.” In database science, IT professionals refer to each row of information in a database as a “record.”4 The term “record” has a different meaning in records management, as discussed above. Keep this in mind when discussing data and information with your IT department to avoid any miscommunications.

Finally, we see that data and information are entered into records, which are maintained as evidence of specific business transacted. We can imagine that this illustration shows the hiring paperwork for Employee #001.

In this database, data could be further manipulated and rearranged to generate new information. For example, we could run a report that can tell us how many employees work on the North Campus (represented by the red chevron) and the South Campus (represented by the gray chevron). This report would be a record made up of information and data from the database.

To summarize, records are made up of information, and information is made up of data. Conversely, data can be manipulated to create meaningful information, which can then be used to create records.


Analysts are often asked how long local governments and state agencies should retain databases. As discussed above, data can be used to create records, but data on its own is not always used to create records. So, the answer to how long to retain databases is…it depends!

The data that lives in databases is useless unless it is structured and presented in a logical, meaningful way by the database interface or reporting system. The data becomes static information once it is used to create a record. Additionally, raw data in a database can be used to create multiple records; you can draw data from a database to produce thousands of unique reports, and those reports would be the records that are evidence of government business. You can think of these reports as containers of information or data at a specific point in time. You may need to retain the raw data in the database as long as it is needed to provide context or validity to these records, but the raw data may not always be a record itself.

For more discussion about the use of data and information outside of records management, see this blog post on the relationship between information governance and records management.


1. ARMA International, Implementing the Generally Accepted Recordkeeping Principles: TR30-2017 (Overland Park, KS: ARMA International, 2017), 2,

2. Ibid., 4.

3. Local Government Code §201.003(8) & Government Code §441.180(11).

4. Ralph M. Stair and George W. Reynolds, Fundamentals of Information Systems, Eighth Edition (Boston: Cengage Learning, 2016), 131.

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