0.6.1 What Is Data?

Data Is Recorded Information

Data is information represented in a form that can be stored, communicated, or processed.

Examples include:

• a player's name;
• a song title;
• a course number;
• a date;
• a price;
• a true/false value;
• a photograph;
• a written review.

Data can describe people, objects, events, measurements, choices, or many other things.

The word is broad because digital systems work with many forms of represented information.

One Real Thing Can Produce Several Data Values

Consider one soccer player.

A system might record:

Name: Jordan
Jersey number: 7
Position: Forward
Available: Yes

Those values are data about the player.

The real person is not stored inside the computer.

The system stores selected representations of information about that person.

This is the same abstraction idea you used earlier in modeling.

Data Has Meaning Because of Context

Consider the value:

7

Without context, you do not know what it means.

It could represent:

• jersey number;
• goals;
• age;
• quantity;
• rating.

Add a label:

Jersey number: 7

The meaning becomes clearer.

Data becomes useful when the system knows what the value represents.

Data Can Be Text, Numbers, Booleans, and More

You have already encountered several simple forms of data:

"Jordan"
7
1.82
true

These can represent:

• text;
• whole numbers;
• fractional numbers;
• Boolean state.

You have also seen data represented as:

• hexadecimal colors;
• UML object values;
• C# values;
• text files;
• URLs and query parameters.

The representation changes according to the purpose.

Data Can Describe Many Records

A system rarely stores information about only one thing.

Imagine a music collection.

It may contain data about many songs:

Song title
Artist
Album
Genre
Release year

Each song has its own set of values.

When information is organized consistently across many similar items, it becomes easier to compare, search, filter, and summarize.

That idea leads into structured data.

Data Quality Affects What You Can Learn From It

Suppose the same artist appears as:

The Example Band
Example Band
THE EXAMPLE BAND
The Example Band 

A person may recognize that these refer to the same artist.

A spreadsheet or program may treat them as different values unless the data is cleaned or standardized.

The usefulness of data therefore depends partly on how consistently it is represented.

Detailed data-cleaning rules appear later in the module.

For now, recognize that inconsistent representation can produce misleading results.

Data Can Come From Many Sources

Data can be:

• entered by a person;
• produced by a program;
• measured by a device;
• imported from a file;
• copied from another system;
• generated by a transaction.

The source matters because it can affect:

• accuracy;
• format;
• completeness;
• meaning.

Do not assume that a value is correct simply because it appears in a spreadsheet.

A Spreadsheet Is One Tool for Working With Data

Spreadsheets make data visible in rows and columns.

That can help people:

• enter values;
• organize them;
• compare them;
• sort and filter them;
• perform calculations;
• create summaries;
• create visualizations.

A spreadsheet is not the data itself.

It is one environment for storing and working with representations of data.

Data Is Not Automatically Information You Need

A dataset can contain many values.

Good technical work still begins with a purpose.

Ask:

What question are we trying to answer?

Then ask:

Which data helps answer it?

Collecting more fields does not automatically produce a better dataset.

Abstraction still matters.

The Main Idea

Data is recorded, represented information.

To work with data effectively, you need to understand:

• what each value means;
• how the values are organized;
• where the data came from;
• whether the representation is consistent;
• what purpose the data is supposed to support.

The next activity focuses on one important difference in organization: structured versus unstructured data.