AI and Big Data – The Two Powerhouses of Industry 4.0

AI and Big data

In today’s digital and data-driven world, it is crucial to understand the roles played by the two big technologies—AI and big data. Even before the word “big data” was coined, it had already taken over the world by accumulating huge volumes of information. If meticulously examined, the data will provide insights about the industry to which it belonged.

The data can be used to make data-driven decisions. However, the task of screening through the huge volume of data and converting it into a format that a computer can understand was too tough for humans to handle. This necessitated the need for artificial intelligence algorithms to perform the tedious task of drawing knowledge from complex data.

As businesses expanded, so did their AI and big data capabilities. Individuals who have completed a professional course in data analytics or business analytics are in high demand. The purpose of big data and AI is to keep pace with and use the huge volume of data that is being generated by smartphones, tablets, and IoT devices.

Understanding what AI and big data really are

  • The digital revolution and massive technological advancements have powered AI and big data. Both of them are also the key drivers of Industry 4.0.
  • The integration of IoT, AI, and big data into the manufacturing environment has created a new era known as Industry 4.0.
  • “Big data” refers to the collection of a huge volume of data that may be structured or unstructured and the extraction of key information from them through analysis for the purpose of providing valuable insights to improve the decision-making process for businesses.
  • AI makes use of several artificial intelligence algorithms to build machines that are capable of mimicking human intelligence functions like learning, logical reasoning, and decision-making.

Big data and its five V’s

Big data has become an information asset for robust decision-making, valuable insights, and process optimization. The characteristics of big data can be studied with the help of the 5 Vs. Understanding the 5 V’s enables big data to be a potent business strategy.


  • This includes the large amount of data that needs to be handled, processed, and analyzed.
  • At present, the magnitude of data used for data analytics and mining is on a terabyte scale.


  • This is the most important “V” from a business perspective.
  • In the ocean of data that exists in today’s digital world, not much of it is used.
  • The value characteristic of big data refers to the filtration of data to get only data that is of real value, i.e., meaningful data.


  • It refers to the high speed of data accumulation and processing.
  • It may take several weeks or even months to process the data and get the results.
  • With the massive and continuous flow of data, it needs to be processed at a fast pace to meet the demands.


  • It refers to the diverse data types that make up big data.
  • This includes structured, unstructured, or semi-structured data.
  • Big data needs to process the different varieties of data either independently or together.


  • It refers to the inconsistencies in data that make quality and accuracy difficult to control.
  • Big data consists of different types of data from various sources.
  • The value of minded data is very high, even though it may or may not directly influence the decision-making process of the organization.

The five V’s indicate that in today’s data-driven world, “big data” refers not only to the collection of a large amount of data but also various processing techniques. It is crucial to quickly identify that portion of data from the vast amount of data that can be used for taking decisions and optimizing the work. This entire process is referred to as “big data.”

Big data analytics

  • “Big data analytics” refers to the use of advanced analytics techniques to analyze large datasets for information that helps businesses make key data-driven decisions about their organization.
  • Using big data analytics, organizations can gain valuable insights such as market trends, customer preferences, unknown correlations, hidden data patterns, etc.
  • This useful data can be used for better decision-making and preventing fraudulent activities.

What is artificial intelligence?

  • Artificial intelligence is a discipline of computer science that involves the creation of application systems that stimulate human intelligence.
  • AI-powered computer systems are capable of logical reasoning and decision-making.
  • The main purpose of artificial intelligence is to enable machines to perform intricate tasks that usually require human intelligence to be completed.
  • AI is presently being used in the user interfaces of several big businesses around the world.
  • Some of the AI-powered virtual assistants that we use in everyday life include Amazon Alexa, Google Assistant, Siri, Bixby, etc.

Big data and artificial intelligence are different yet closely intertwined with each other.

  • Both AI and big data share a symbiotic relationship with each other.
  • Organizations are using big data to train AI algorithms and, in turn, using artificial intelligence to understand big data.
  • Many businesses are not realizing the benefits of combining AI and big data.
  • Data with AI is meaningless. Also, without AI, mastering data is impossible.
  • “Big data” refers to the initial, unprocessed input data that needs to be sorted, organized, and integrated before it can be used.
  • On the other hand, artificial intelligence is the final product of data processing.
  • AI when applied to big data helps in identifying anomalies, pattern recognition, and determines the probability of future outcomes.
  • Although fundamentally different, both big data and artificial intelligence complement each other perfectly.

Industry applications of big data and artificial intelligence

Here are the various industries that utilize AI and big data:

AI and big data in the development of autonomous vehicles (AVs)

  • With big data and artificial intelligence, AVs are capable of handling fundamental driving tasks with minimal or no human intervention.
  • AVs built using advanced technologies such as AI, big data, and IoT can cause significant disruption in the transportation sector.
  • The AI software that forms an integral part of AVs evaluates billions of data points each second using inputs received from GPS, radar systems, cameras, advanced sensors, etc.

AI and big data in healthcare

  • Big data and artificial intelligence are transforming healthcare and improving the quality of services offered to patients.
  • From preventive healthcare and in-patient mobility monitoring to healthcare virtual assistants for providing support to healthcare providers remotely, big data and artificial intelligence are transforming the healthcare sector.

AI and big data in industrial automation systems

  • Industrial automation is a key field where AI and big data are being implemented.
  • With these two technological advancements, machines are becoming more intelligent than before.
  • The use of machines is no longer confined to just performing repetitive and easy tasks.
  • Intelligent machines can work with humans on production lines.

There is extensive research going on in AI and big data. Both of these areas are inseparable from each other. Both big data and artificial intelligence are key aspects of the Industry 4.0 paradigm and also the driving forces behind it.

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