Data areas are fundamental building block of data. They are so necessary that analysts in various disciplines have appropriated lock to satisfy the requirements of their usage cases. Though this applications are a testimony to the value of a data field, they create confusion regarding the precise definition behind them.

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The objective of this post is come (1) clearly define data fields, (2) list different types, (3) present how they are used in databases and programming languages, and (4) work out confusion around “data field” and also “field data.”

If you job-related with data in any means — native data entry to data science — this short article is for you.

Data ar Definition

A data ar is a place for a predetermined kind of data that — jointly with other data areas — describes the ar it is stored. The most usual example is a pillar in a data table that explains the row v which it intersects, and also others include class variables in programming language such as Java.

A simple means to think about data areas is come imagine an item and define multiple instances that it. Because that example, let’s take beds. One bed is king sized, do of wood, and also uses spring suspension. Another bed in queen sized, do of metal, and also uses elastic suspension.

Beds space the object, if size, material, and also suspension type describe the beds. As soon as we write these down on paper or go into them in a database, we’ve produced a location because that the 3 descriptions, and castle are now fields.

Data fields are also known together data attributes, data traits, and data characteristics.

Data ar in a Database

The fundamental kind of data is data tables. Lock consist the rows that we contact records (or “tuples” if you’re fancy) and columns. The an initial column is composed of unique IDs that the objects we are going come describe, and also the columns save on computer information about it.

NOTE: over there is some dispute as to whether the very first column should be thought about a ar or simply the “unique ID.” due to the fact that by meaning fields describe the place they room stored, us could think about the distinct ID either a titular summary of itself, however it’s more intuitive to i think it’s simply the place described by the fields.

Using our instance of beds, here’s a sample table:

Bed (Unique ID)Size (Field)Material (Field)Suspension (Field)
Bed 1KingWoodSpring
Bed 2QueenMetalElastic
Bed 3TwinMetalSpring
Bed 4DoubleMetalSpring
Bed 5CribWoodSpring

Now it should be clear what a data field is, therefore let’s revisit our definition: a ar for a predetermined kind of data the — collectively with various other data fields — describes the place it is stored.

In this example, the location is a column, the type is size/material/suspension, the collective is those 3 together, and the place described is the row’s bed.

It’s necessary to keep in mind that a field is not the separation, personal, instance data entries (“King,” “Metal,” “Spring”). That is the obelisk as a whole, in this situation the dimension field, product field, and also suspension field.

In the context of a database, columns and fields space synonyms.

Examples of Data Fields

Simple instances of data fields include weight, color, date, sales, averages, member ID, promotional code, status, paper type, keyword, and rainfall. Any item of info that deserve to be offered to define an object, event, or idea have the right to be a data field.

That may sound silly, but it’s actually what provides data fields so flexible and also so an important — nearly anything in the natural and human human beings can be a data field.

Data field in Excel

In Excel, a data ar is a pillar in any type of data table structure developed with cells. That is simplest to identify when we’re making use of the Excel’s Data Table function (Insert > Tables > Table), but any type of column in a row-by-column table deserve to be a data ar — also a an easy range.

Data Fields and Data Records

The 2 dimensions the a data table consist, together we know, that rows and also columns. Rows are referred to as records due to the fact that they consist of one instance of the distinct ID and also each field.

You’ve more than likely heard the word “record” offered all your life there is no realizing the this is what the refers to.

A record is nothing an ext than a complete row the data. Police records, sporting activities records, college records, and geographic records are all examples are rows in a database. A institution record might look like this:

Student NameGPAAttendance (out that 180)Average tardiness# of extra curriculars
Jane Doe3.51755 min3

The first (top) row is recognized as the header since it mirrors the “head” of the human body of information in every one of the adhering to rows. This is important due to the fact that it moves our focus from the entirety table in the direction of rows. A document is one instance of what the table tells us — the basic of the table.

If we only saw one record, we might infer the remainder of the data table. However, if we just saw one field, we would certainly not have the ability to infer the rest.

Collection the Data Fields

You may have actually heard the expression “a arsenal of data fields.” A heat is a repertoire of data fields in a data table. The cell wherein a ar intersects with a record is the “place” it defines — the distinctive ID of the record. In this sense, a document is a “group” of fields.

Types of Database Fields

Database areas are not all make the same. In general, they fall into six types: (1) dates (2) numbers, (3) strings, (4) Unicode, (5) Binary, and also (6) miscellaneous. In most cases, this is what you will encounter together a data analyst since the differnet subtypes often tend to be facility and require understanding of computer systems. However, because that the sake of completeness i list them every below. Here’s a perform of various data types with short descriptions:

All values in a given ar will it is in the same type. This is a an essential principle of data quality. If your areas contain data of various types, then you can not filter on qualities or manipulate measures.

Numeric areas Are Measures, not Attributes

Numeric field varieties are special due to the fact that they behave in different way from the other types. Text and also other data types are considered attributes because they cannot be manipulated across or down the data table. We deserve to only counting the variety of times they appear or filter the data ~ above them.

Numbers, however, have the right to be added, subtracted, multiplied, and divided across and under the table. This method they space dynamic, and we refer to them as measures quite than attributes.

For example, imagine we add another ar to ours dataset on bed for weight as shown below. We could add the weights the Bed 1 and Bed 2 come arrive at a brand-new value, 185, since it is a measure. However, us cannot manipulate words to arrive at brand-new values. We have the right to only consolidate rows based on them, which provides them attributes.

Bed (Unique ID)Size (Field)Material (Field)Suspension (Field)Weight in KG (Measure)
Bed 1KingWoodSpring90
Bed 2QueenMetalElastic95
Bed 3TwinMetalSpring85
Bed 4DoubleMetalSpring80
Bed 5CribWoodSpring50

Data field Mapping

Sometimes we desire to consolidate lot of data tables right into one, and also these tables concern the same distinct IDs however are no labelled or normalized in the very same way. Data field mapping is an task that outlines just how the areas from 2 or more starting tables will be consolidated into a brand-new table.

For example, consider the following two tables indigenous a book store database. In the first, we check out that BookID is repetitive multiple times to accommodate the months as soon as it was confirm out. This way BookID + Month is the distinctive ID because that this table, since we might otherwise simply add the number of checkouts every book.

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In the second, we can see that BookID is occasionally repeated because that multiple editions, such as AY135 in heat 4. This method that the ISBN number is the unique ID for tower 2.