What is Big Data? | How does Big data processing works and big data characteristics?

What is Big Data? | How does Big data processing works and big data characteristics?

When you listen Big Data you may think, How big is big data and why it is so important and what is big data computing.

Is this a tool? Is this technology? 

Artificial Intelligence and Machine Learning technologies greatly simplify the process of collecting and processing big data.

In this article, you will learn about Big Data and the terminology used in Big Data and how to do big data processing and what is big data characteristics.


What is big data


Big Data

Big data is a collection of data that is too large and complex for traditional data processing and data management tools.

 Technology has made large-scale data management and analysis possible for all of us.

Big data is the primary information that emerges as a result of consumer interaction.

Before you get into big data, you need to know first, What is Data?

Data is the information which can be read, write and can be processed.


What is Big Data?

Big data is a high-capacity, high-speed and diversified information that requires specific, cost-effective and innovative forms of information processing to improve decision-making and automation. Big data is data, but it is a large collection of data.


Usually, this is beyond the ability of traditional database management and editing.


Big data is a complex technology that includes other technologies such as artificial intelligence or machine learning.


Big data is growing “fast” every day,In other word, Big data is a data which is diverse, large, and fast. This data set is so large that traditional software cannot process it.


But this large amount of data can be used to solve business problems that you could not solve before.


This is a large amount of data and complexity that no traditional management tool can store or process.


Traditional data is easy to process but it is not easy to process Big Data.


NSE Exchange is an example of big data, which generates approximately 1 TB of new transaction data every day.


Data on a Social Media platforms is one of the form of Big Data.


Three Vs of big data or Characteristics Of Big Data

These are the main characterstics of big data: 






big data characteristics


Volume: The volume of data is important. This can be anonymous data, such as a data channel on Facebook or streams on a web page. You have to process large amounts of  low-density and unstructured data.


big data characterstics - Volume


Velocity: Velocity is the speed at which data is received and (possibly) processed. Typically, the maximum data rate in memory is higher than writing to disk.


Variety: Variety means the multiple types of data. With the growth of big data, data is coming into new types of unstructured data. Big data includes many types of data, which can be structured, unstructured, and semi-structured.


big data characterstics - variety


Value: Data has its own meaning and value. But this value was useless until it was discovered. This is also important: how accurate is your data and how reliable is it?


The value of big data is not limited to its analysis and big data characteristics are very important to analysis of data.


Veracity: Truthful of the data is the key part of the Big Data. Data should be the accurate and useful for business.  


Big data advantages:


Big data allows you to get a full report because you have additional information.


Big data can help solve many business endeavors, from customer experience to analysis.

Product development

Customer Experience

Fraud and identity

Machine learning ML (Machine learning is now a hot topic.)

Operational efficiency

Stimulate innovation



Big data type

Big Data Types

There are the following types of big data:

Structural Data

Unstructured Data

Semi-structured Data


Structural Data: Any data that is stored, available, and processed in an approved format is called “structured” data.


Unstructured Data: Any data of unknown size and structure is considered as unstructured data.


Semi-structured Data: Semi-structured data can take both forms.

What is big data analytics?


Big data analytics is the application of advanced methods of analysis to a very large, diverse set of data, including data from different sources and terabytes to zetta bytes.


Organizations now have a lot of data, but they do not know how to get its meaning, because this data is in its original form or unstructured.


Advantages Of Big Data Processing

Big data offers you new opportunities and business models.


With the help of big data Businesses can use external intelligence to make decisions for there product, services and business strategies.


You can improve your services and product by processing the big data available to you.


By using social media data and other platform data to make best decision and utilize the human behaviour for your business.



Big data challenge


Although big data has a bright future, it also have some challenges.

Collecting and combining different data is a very difficult task.


Despite the development of new technologies for data storage, the volume of data will double in about five years. This is the big challenge for big data.

But just storing data is not enough processing the data that is relevant to customers and allows value analysis requires a lot of work. Still big data technology is changing rapidly.


New strategies and techniques are needed to analyze large data sets.


Poor or inaccurate data will lead to inaccurate results or predictions, which will only waste people’s time and energy.


How big data processing works


Consolidation: Big data combines data from many different sources and applications. During integration, you enter and process data and make sure it is in a format and accessible that business analysts can use this data for a valuable output or product.


Management: Big data processing system Requires large data storage. Your can utilized the cloud storage or your own storage for big data. You can save the data in the form you want and, if necessary, add the necessary processing tools. Cloud is becoming more and more popular because it supports your current computing needs and enables you to activate resources on demand.


Big data Analysis: When you analyze the data and take action, your investment in big data will be rewarded. Research the data to find new ways. Use machine learning and artificial intelligence to create data models.



Big data source

Social media

Users of social media like Facebook, WhatsApp, Twitter, YouTube and Instagram generate a huge data such as uploading photos, videos, sending messages, posting comments, likes, etc.


Jet engines in aviation

Consumer feedback

IoT tool (IoT Devices)






Applications of Big Data


Big data can process large amounts of information quickly, but what does it mean for businesses? This is the use of big data:-


Banking and securities

Stock Exchange

Social media

Meteorological satellite

Internet of Things (IoT) devices

Health care providers








Location control

Financial services








Q1. What makes big data so important?

Ans. The true value of big data is measured by how well you can analyze and understand it.



Q2. What is big data in simple terms?

Ans. In short, big data is larger and more complex data. These data sets are so large that traditional data processing tools cannot manage them.


Q3. What is big data and how is it used?

Ans. Big data includes all possible structural and non-structural potential data from a variety of sources.

Q4. What is big data answer?

Ans. This means a large amount of data that will grow exponentially over time. It is so large that it cannot be analyzed using traditional methods of processing or data processing.


Q5. What is the definition of big data?

Ans. Big data is a large, diverse set of information that is constantly growing.The definition of big data is to include more types, quantities, and faster data. The combination of these characterstic data is called big data. Large data is defined as “large” not only in size, but also in terms of variety and complexity.

Q6. What is data mining?

Ans. Data mining is the process of obtaining meaningful data to help you make business decisions to reduce costs and increase revenue.


Q7. Who is data scientist?

Ans. Simply put, a Data Scientist is a person who specializes in the art of Data Science.


Q8. Who is data analyst?

Ans. who analyze the data understand the data and act as data protectors for the organization to make strategic decisions.


Q9. Who are the big data companies in the world?

Ans. List of Top Big Data Companies



Happiest Minds


Indium Software



Spec India

Sigma Data Systems

Which is the best platform for big data?

Ans. Hadoop MapReduce is the best platform for big data

Q10. What are the five Vs of Big Data?

Ans. The five Vs of big data




value and 



Volume- amount of data from different sources

Velocity- the rate of data increasing.

Variety: Multiple data types structured, semi-structured, unstructured

Veracity-the credibility of the data authenticity

Value- data is capital here.


Q11. What are the main components of big data?


  • Machine learning (ML)
  • Cloud computing
  • Business intelligence


Q12. What are the types of big data?


  • Structural Data
  • Unstructured Data
  • Semi-structured Data


Q13. What are the 3 types of big data?


  • Volume
  • Velocity
  • Variety


Q14. What is Hadoop?

Ans. Hadoop is an open source Apache source and is used to process and analyze very large amounts of data.

Modules of Hadoop



Map Reduce

Hadoop Common

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