A Foolproof Guide On Different Types Of Data Used in Various Field

Whether you are working as a businessman, running an organization, or working as a data scientist, marketer, or any other kind of professionals who need to work with different kinds of data, you need to be familiar with all types of data.

While studying the types of data, the first question arises what is the need to understand the types of data? Well, there are different classifications and types of data. Understanding their classification and types allow the data professional to use the correct measurement and thus help them in making the correct decision. Here in this guide, we are discussing different types of data and many more about data.

Types of data in the Computer

In Computer science and programming, the data are divided into basic Five categories which include integer, floating-point or decimal number, string, character, and Boolean. The different types of data are represented differently in the computer and the devices require different amounts of memory to store these kinds of data.

Also, these data have varying activities and operations that can be performed upon them. The operation can be performed on one kind of data, that cannot be performed on another data type. For example, it is possible to calculate the square root of integer type data but it does not make sense when the same operation is tried to perform on character type data.

types of Data

The main type of computer data includes numbers, characters, and logic.

Number

The number type of data is further classified in integers data type and floating number data type.

Integer:

Integer data type or the whole number data type includes binary values. This number is not having any fraction and is a whole number digit. For example 2, 4, etc.

Floating number:

While the floating number data type is a kind of data that has a fractional part and they are generally represented with the help of two components. The two components of the floating number data type include the main part and the fractional part and they all are binary numbers.

Character and String

In Computer science, every digit, letter, and punctuation mark is considered as a character. Along with these, there are some invisible characters also that include tab, space, and carriage-return character.

Character set:

The character set can be defined as every value that represents a single character which is having its own binary pattern.

String

The String data type can be defined as the data value that is build up by a particular sequence of characters. The String data type can have any sequence of bot visible as well as invisible characters and they may be repeated in the string data set.

Constants and variables

In a computer program, the data type can be constant or variable.

Constant data

The data type is defined as constant when the same kind of data is repeated. For example, when only integer datatype is repeated is considered as constant data.

Variable data

While when the user asks different questions then there will be variable kinds of data. For example, when users ask for age, there will be a number data type and when the next question is Gender, then there will be character or string data type.

Types of data collection

Data collection refers to the gathering of quality evidence in order to get the answer to several unanswered questions along with help in predicting the future trend. The methods for data collection are as follows:

Interview

It is a data collection method where there is a face-to-face conversation between two peoples whose only purpose is to collect the relevant information for the research work.

Questionnaires

In this method of data collection, several questions are asked to the individual in order to collect relevant information. The Question can be asked directly or via any instrument or tool.

Reporting

In this method, data is collected and then submitted for further analysis. The main purpose of the reporting data collection method is to collect only the most accurate data and thus a more effective decision-making process.

Existing data

The existing data refers to the data which are already present in the records> This kind of data is generally used to add measurement to the research.

Observation

In this method, data is collected by observing any activity or work. This kind of data collection method is more subjected to accuracy.

Types of data in data mining

Data mining can be defined as the process to collect potentially valuable data or large data sets. On the basis of data mining, data can be of various types. following are some data types on the basis of data mining:

types-of-Data

Relational database

When any set of databases which is having a link with some pre-defined constraints then it is known as relational databases. They are generally arranged in rows and columns.

Data warehouse

When the data is mined using some set of rules is known as a data warehouse. In this data mining method, data is collected from several heterogeneous sources and thus allows the users to perform analytical reporting, standardization, and then the ad-hoc request, and in last the decision making.

Transactional database

In the transactional data mining process, there is a need to first check the transaction entitles. We can describe the transaction method as a sequence of activities that are both dependent and independent at the same time.

DBMS

A database management system or the DBMS is a process for the development and management of data. It is a structural way for the creation, retrieval, updation, and management of data.

Advanced database

Advanced databases system like NoSQL and new SQL are specialized types of data mining methods.

Types of data in data science

In data science, there are two variables of data. These are:

Numerical

The numerical data type can be described as the value which can be measured and they are generally represented in the form of a number.

Categorical

The categorical data type is not a measurable value and is generally in the form of text and data. It is possible to break the categorical data into nominal and ordinal values.

Types of data in research

On the basis of the collection, the methods are mainly of four types. The data collection method includes experimental, observational, simulation, and derived. The management and processing of data are also get affected by the method you choose for the collection of data.

Observational data base

When the data is collected by observing the activity and the behavior of the process then it is known as observational data collection.

Experimental database

When the data is collected by active intervention and experiment then it is known as experimental data collection.

Simulation data

Simulation data refers to the data collection method where data is generated by imitating the activities and operations that use to happen in real-world systems with the help of a computer test model.

Derived database

The derived data collection method or the compiled data collection method involves the collection of existing data which are often collected from different sources. And, the collected data is again used in order to generate new data via transformation.

Types of data in Statistics

In statistics, there are generally four types of data. They are nominal data, ordinal data, discrete data, continuous data. There are two additional categories of data type also in statistics. These are Quantitative data and Qualitative data.

Type-of-data

Quantitative data

Quantitative data can be defined as the data type which can be measured in amount or volume. These are generally measured in number or we can say this data type can be measured.

Qualitative data

This data type cannot be described or measured in number instead it refers to the quality of the data. It includes how useful the data type is.

Nominal data

This data is a simple data type that is generally used in labeling the variable. The term nominal derives from the name which means it is used to label the data type without using the quantitative value.

Ordinal data

The ordinal data type mentions the number of the data where it is present in order. This is a type of data when the data set is placed in some type of order and the ordinal data mentions the position of the data set on the scale.

Discrete data

This kind of data only involves integer values and these values can not be divided into parts. We can explain this with an example like the number of students in the class. It can be fractional like there are no 1.5 students in the class.

Continuous data

This is a kind of informational data that can be categorized into the finer level. It is possible to measure the continuous data in scale and they have only the numerical value.

5 types of data most commonly used in analysis by marketers

The data type which is generally used by the marketers is nominal data, categorical data, ordinal data, continuous data, and interval data. The above mentioned four data type has already been mentioned int he above sections. While the interval data type can be defined as the units which are used for differentiating the different type of data.

Different types of data in six sigma

In six sigma, there are basically two types of data. These are Qualitative data and quantitative data.

Qualitative data is a subjective type of data that cannot be measured and is generally used for defining the quality of the data.

While the quantitative type of data can be defined as the data type which can be measured in numbers. It is possible to order and rank the data and thus measure them easily in numbers.

Types of data analysis

The analysis method for the data is categorized into 6 different types. These are:

Descriptive analysis

The goal of this analysis method is to describe and summarize the data. It is generally the first step in analyzing the data type.

Exploratory analysis

In this analysis method for the data, the goal is to explore and examine the data and then figure out the relationship between different variables which was not known before.

Inferential analysis

The goal in this data analysis type is to get the information about the large population using a small sample of data. It is itself statistical modeling and it involves the use of small sample data in order to get the information regarding the large population.

Predictive analysis

This data analysis type is useful for finding the patterns in the historical and current data in order to make future predictions.

Casual analysis

In casual analysis, the aim of the analyst is to figure out the cause and the effect of the relationship between a different variable and then it focuses on figuring out the cause of the correlation.

Mechanistic analysis

This data analysis method is useful in understanding the exact changes in the variable that further leads to the changes in other variables.

Types of data structure

Data structures are specialized types of structures that are helpful in organizing and storing data in a computer in the way in order to perform activities on these data in the future. They are generally of 8 types. These are Arrays, Linked lists, stacks, queues, hash tables, trees, heaps, and graphs.

Read all types of data structure here All types of data structure you should know

Types of data visualization

Data visualization is the method to represent data in either graphical or pictorial format. The most common method for the data visualization involves column chart, stacked column chart, bar graph, stacked bar graph, area chart, line graph, dual-axis chart, mekko chart, waterfall chart, pie chart, bubble chart, bullet graph, heat map, funnel chart, and scatter plot chart, etc.

Types of data storage

Data storages are specialized drives or storage devices that are used for the storage of large databases. They can be physical devices or can be cloud drives. Generally, there are two types of data storage. These are:

Direct Attached storage

As mentioned in the name, this data storage refers to the type of storage that can be physically connected to the computer device. This kind of data storage is generally useful in accessing only a single machine at a time. Examples of this kind of data storage include Hard drives, solid-state drives, DVD drives, flash drives, and many more.

Network attached storage

This data storage type allows being used in multiple storages at a time. They’re not physical devices instead are cloud or network-based data storage that can be accessed from any computer.

Types of data model

The data model can be defined as the logical structures which are helpful in the creation of the databases. There are four types of data models. These are:

Hierarchial model

In this kind of data model, the databases are arranged in the form of a tree-like structure where there is a single root and the data are linked to one base root.

Network model

In the network model, there is a networking type of representation of the databases where the relationship between different variables is also shown.

E-R model

This type of data model is useful in describing the structure of the data with the help of an entity-relationship diagram. It can be referred to as the blueprint of the databases which can be further used for the implementation of the large datasets.

Conclusion

So these are types of data divided into different categories on different bases. And, understanding all types of data helps the data professional in picking up the most suitable data type in order to take the correct decision.

FAQs

What are 2 types of data?

In general, the databases are categorized into two types. These are the Quantitative data type and the Qualitative data type.

What are 4 types of data?

Databases on the basis of statistics are generally categorized into four types of data. These are Nominal data, ordinal data, discrete data, and the continuous type of data.

What are the 5 types of data?

In the COmputer program, databases are generally divided into five types. These are integer data type, floating-point number, character, string, and Boolean.

What are 6 types of data?

In statistics, databases are broadly divided into six types. These are Quantitative data type, Qualitative data type, Norminal data type, ordinal data type, discrete data type, and continuous data type.

What are 3 types of data?

The three types of data include short-term data, long-term data, and useless data. Short-term data are typically transactional types of data that can be used once and never be used again. The long-term data type is a certificate type of data that can be used for a long time. The databases are very large and also contain a large volume of useless data which cannot be used.

What is the most common type of data?

The data types which are used most commonly include nominal data, categorical data, ordinal data, discrete data, dichotomous data, and discrete data.

Frequency distribution may be used to describe which type of data?

Frequency distributions are used for representing graphs including line charts, histograms, bar charts, and pie charts. They are generally useful in describing both the quantitative as well as qualitative data types.

Working as Freelance Content writer. Have great experience in creative writing for different Niches. Worked as Assistant Editor and Communication Manager for Metro Rail News Magazine. I am also very much interested in data science, data analytics, big data. Thank you.

Leave a Comment