Data, Information & Metadata

Pin down the three terms the exam tests on sight — data, information, and metadata — and explain why managing metadata matters as much as managing the data.

The three terms everything else is built on

A database is an organized collection of logically related data. Notice the definition says nothing about size or complexity — a contact list on a phone is a database, and so is a bank's transaction store. The load-bearing words are *organized* (intentional structure) and *logically related* (the data share a purpose).

Three terms get conflated constantly, and the exam exploits exactly that confusion. Get the contrast crisp:

- Data are stored representations of objects and events that have meaning and importance in the user's environment. Data are not just numbers and text: modern databases also store structured data (numeric, character, dates in tables) and unstructured / multimedia data (images, video, documents, GPS traces). - Information is data that have been *processed* — given context, summarized, or interpreted — so as to increase the knowledge of the person using it. - Metadata are data that describe the *properties or characteristics* of end-user data and the context of those data. The one-line memory hook is “data about data.”

Worked example: data vs. information

Take a registrar's raw output:

1001  3.7
1002  2.9
1003  3.4

Those two columns are data — stored representations, but no context tells you what they mean. Now process them: pair each ID with a name, the course they're enrolled in, their major, and a heading.

Class Roster — COMP 378, Section A
ID    Name        Major              GPA
1001  A. Okafor   Computing Science   3.7
1002  B. Singh    Information Systems 2.9
1003  C. Ramirez  Computing Science   3.4

The *same values* are now information: summarized, contextualized, ready to inform a decision. Processing is the dividing line, not the values themselves. (In practice databases store both — many even pre-summarize data so they are already information.)

Worked example: metadata

For the GPA column above, the metadata are the facts that describe it, not any student's actual GPA:

Data Item   Type      Length   Min   Max   Source
GPA         decimal   3        0.0   4.0   Registrar system

Without that descriptive layer, GPA = 92 looks fine until you learn one system stores GPA on a 4.0 scale and another on a 100-point scale. Metadata is what lets you tell those apart — which is why managing it is *at least* as important as managing the data itself.