Data Classification: Meaning, Types, and Importance

Data classification is the process of organizing data according to relevant categories for efficient usage. It helps to locate and retrieve data quickly. This process is vital when it comes to security, compliance, and risk management.

Classification of data meaning, tagging data so that it can be easily tracked. Moreover, it eliminates duplicate data which frees up storage space, lowers backup cost, and accelerates the search process. 

What is Data Classification?

• It's the process of categorizing data into homogenous (similar) groups based on shared properties.

• Raw data is difficult to comprehend and is unsuitable for further analysis and interpretation. Data organization aids users in comparison and analysis.

• For example, a town's population can be divided into groups based on sex, age, marital status, and other factors.

Types of Data Classification

There are three types –

1. Content-based classification stands for categorizing data based on the sensitivity of the information it contains.

2. Context-based classification stands for segregating data based on its application, location, its creator, along with other factors like characteristics of the information and indirect indicators.

3. User-based classification is an entirely manual process. It depends on the decision of users on how they want to tag each data. 

Data Classification Methods

Some of the most significant methods are –

1. Manual interval

2. Defined interval

3. Equal Interval

4. Geometrical interval

5. Quantile

6. Natural Breaks

7. Maximum breaks

8. Standard deviation

Objectives of Classification of Data

Its objectives are –

1. Simplification: It helps to present data concisely. Hence, it becomes more convenient to analyze data.

2. Improves Utility: Classification brings out the similarity in different sets of data, which enhances its utility.

3. Brings out Individuality: Classification of data in statistics helps in grouping them in various subheads. This process brings out the uniqueness of each data and assists in its better study. 

4. Aids Comparison: It facilitates easy comparison with a substantial volume of data.

5. Increase Reliability: Classification is a scientific process, and its effectiveness is proven. Therefore, this process increases the reliability of a specific set of data.

6. Make it Attractive: One of the main objectives of data classification is to make it more attractive and enhance its presentation value.

7. Consolidation: Consolidate a large amount of data so that similarities and differences may be rapidly identified. As a result, figures can be grouped into parts based on common characteristics.

8. Priority: To prioritize the most important data while segregating the unnecessary bits.

9. Statiscal Analysis: To enable statistical analysis of the collected materials.

Characteristics of an Impressive Classification

• The primary feature of proper classification is that it makes the data comprehensive. It will cover every item in a set and segregate them into appropriate groups.

• Every data set lacks clarity owing to its volume. This classification brings much-needed clarity and makes it easier to navigate.

• Data in a set is often scattered in various places. Classification brings similar information under a single group and improves homogeneity.

• Every impressive classification must have elasticity, so that, if the purpose of classification changes, the basis of it can change easily.

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Classification Methods

The following are the classification criteria:

Classification by Location

• Geographic classification refers to the classification of data based on geographical places such as countries, states, cities, districts, and so on.

• It's also referred to as ‘spatial classification.'

Classification Based on Time

• A chronological classification is one in which data is classified according to the passage of time.

• Data is arranged in ascending or descending order according to temporal units such as years, quarters, months, weeks, and so on in this classification.

• Temporal classification is another name for it.

Classification in Terms of Quality

• Data are classified using this method based on features or qualities such as honesty, beauty, intelligence, literacy, marital status, and so on.

• For instance, the population can be segmented based on marital status (as married or unmarried)

The Classification that is Quantitative

• This classification is based on measurable parameters such as height, weight, age, wealth, student grades, and so on.