It is very much important to know that what are the categories of a data set, because by this only you will understand that for what the data is all about.

 

You will always need to figure out that in which category my data falls in, because by this only you will get to know that what are the things to discover on data.

 

It is like gaining the knowledge of categorizing data precisely for doing the proper data analyzation.

 

1. Attitudinal Data.

 

The word ‘attitudinal’ is derived from the word ‘attitude’ means that what is the person’s posture of mind. In this case we can call person a customer.

 

Whenever we get data about customers, we can predict the likes and dislikes of the customer, that which types of products is most purchased on what circumstances.

 

We get to know about the customers insight through data, we learn that what is the attitude matrix of the customer, which includes; likes, dislikes, comments, amount, purchasing pattern, seasonal effects, feelings & emotion etc.

 

2. Identity Data.

 

These types of data deals in the personal information of customer such as name, mail ID, phone number, address, IP, location, Government identifiers, Nationality ID.

 

This data is used to verify the customer which decreases fraud and scams, also used as exact match identifier.

 

This Data is used as the identifier and verifier and to make sure that customer is not a bot.

 

3. Behavioral Data.

 

Action taken by customers such as clicks, views, purchase session. This data is used to record the behavior of person’s action taken to buy product or services.

 

This data tells the behavioral pattern like clicks, page views, video plays, add to cart, purchases.

 

Later this data is used to analyze the behavior of customer towards any specific product or services.

 

4. Customer Data.

 

Data, which is based on customer identity like product purchased, transaction detail, frequency of purchasing, support tickets, service requests.

 

This type of data carries almost every information about customer which is needed for further analysis later, these data tell us about things like platforms used for purchasing and transaction; also tells us about the age, gender, and demographics.

 

5. Feedback Data.

 

These type data we mostly collect from surveys, comments, rating, opinion poll, etc.

 

It is the customer, who by itself tells us about the opinion of any product or services.

 

We get to know about that what are the problems in product and services is and how to improve its quality, and some other things like customer satisfaction, product development.

 

6. Financial Data.

 

Almost every corporate sector like firms, organizations, industries, startups, and businesses uses and maintain their own financial data which carries the record of their transactions, assets, liabilities, income & expenses, equity, etc.

 

These data later used for the analysis of decision making, performance tracking, risk management etc.

 

This data describes about the monetary activities and economic position of individual or organization.

 

7. Interaction Data.

 

These data are based on communicational exchanges, touch points between people and systems, it tells us about the engagement rate of the customer, employee or individual with brand, product, or services.

 

This data tells us about the who, what, when, and how of the interaction.

 

When we analyze these types of data we get know about the customer operational experience and its analytics.

 

8. Operational Data.

 

Operation data covers the day-to-day records of activities and transaction that keep up running the organization.

 

Its main task is to record the supply chain workflow, inventory, customer interaction, and business processes.

 

This data tells us about the efficiency, decision making, optimization and the health of organization’s daily functioning.

 

9. Transactional Data.

 

Data which carry all the information of the transactions like confirmed and pending purchases, shipments, service interaction, and event detail and point of sale.

 

We use this data, which tells us about the operational tracking, financial reporting, customer insights and how to avoid risk.

 

It is a factual data which is based on forming the backbone of financial and customer analytics.

 

10. Unstructured Data

 

These types of Data are also known as messy data with improper formats like pdf, emails, scanned documents, reports, transcripts, and many other formats.

 

In these types of data, we need a lot of cleaning, changing format, removing unnecessary spaces and marks, and then making it valid for proper data analyzation.

 

These data types are unorganized, which is always needed to be processed before analyzation.

 

Conclusion.

By integrating these data types of data, one can create a better understanding in data sets and can create a personalized report for organization.

 

By implementing a proper data analysis on above data type, one can create great reports, presentation, graphs, tables to visualize the data properly.

 

Data types like these are found in almost every corporate sector, if you carry good knowledge on these data types, then categorizing data will be much easier for you.