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As the name implies, AI stands for Artificial Intelligence, also known as synthetic or man made intelligence. One of the many branches of computer science is artificial intelligence. There are computers that can carry out a range of tasks that would usually require the human brain. The growth of deep learning and machine learning goes hand in hand with developments in artificial intelligence.

Significant changes in the technological sector, especially in AI, are brought about by the growth of these two. It’s often referred to as machine intelligence. It was established in 1956 and has received a significant amount of funding since then. Huge amounts of money were squandered but they pale in comparison to the success that the world has made with AI. It is also known as robotics because it is the best representation of human intelligence by machines. It does not, however, revolve exclusively around that. Reasoning, understanding and representation are only a few of the obstacles or problems that artificial intelligence faces. It operates with a variety of tools and applications and is made up of a variety of software and programmes written in a variety of programming languages that run on a variety of systems.


Big data, as the name implies is a vast volume of data that must be processed, analysed and worked with in order to generate valuable results that will assist in an organization’s overall development. The three Vs, or Volume, Variety and Velocity are widely used to characterise big data. The sum of data is referred to as volume. Finally, velocity refers to the rate at which new data is produced on a regular or daily basis. Variety refers to the various types of data that are available.

Big data analytics solutions have evolved dramatically in recent years. This is due to the fact that big data is much too large for conventional software to handle. Furthermore, big data faces numerous challenges, including collecting, exchanging and analysing data, among others. There are three different types of big data: structured, unstructured and semi structured. The first has a distinct format, while the second does not and the third is a hybrid of the first two. Because of the advantages that big data consulting services have brought to the market, they are in high demand.


  1. For big data analytics solutions, AI brings new methods. Previously, people analysed data using MySQL but artificial intelligence and machine learning have introduced new and advanced methods of analysis, or rather, they are new methods. Machine learning and artificial intelligence are the results of combining statistical methods with computer science
  2. With AI, the duration of labour is reduced. Human capital will now devote their resources to greater and more important activities because computers are doing the majority of the job. Furthermore, AI can complete these tasks in a fraction of the time that humans can
  3. Humans are still extremely important. AI and machine learning and other emerging technologies are critical in assisting companies in gaining a more comprehensive view of all of the data by allowing them to link key data sets. However It is not a question of suppressing human intellect and insight. To augment these technologies companies must combine the power of human intuition with artificial intelligence. To be more precise, an AI system must be able to learn from both data and humans in order to perform its work


As AI is an invention that attempts independent functioning similar to human intelligence through task automation and outcome prediction, big data collection is seen as the future of responsible AI development. AI, on the other hand, does not try to mimic human intelligence’s cognitive reasoning, instead relying on experience of data patterns and computational resources to carry out its functions. As a consequence, Big Data and Artificial Intelligence are working together

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