Big Data and AI are two of the most popular and useful technologies today. Artificial intelligence is in existence from more than a decade, while Big Data came into existence just a few years ago. Computers can be used to store millions of records and data, but the power to analyze this data is provided by the Big Data.
We can say that together Big Data and AI are set of two amazing modern technologies that empower machine learning, continuously reiterate and update the data banks, and taking the help of human intervention and recursive experiments for the same.
The business scenario has changed a lot in the past few years, with disruptive technologies making inroads into it. Big Data and Artificial Intelligence are perhaps two of the most widely adopted innovations in the business world today. Big Data refers to the huge volume of data, both structured and unstructured, that is gathered from diverse sources and serves powerful insights for the business when analyzed. Artificial Intelligence, as the name suggests, is a set of technologies which enable machines to replicate human intelligence in terms of learning, evolving, and decision-making in the absence of human intervention.
Big Data and AI are seemingly two different technologies that bear no resemblance to each other; but surprisingly, the two of them share a symbiotic relationship, where each one drives the other in one or more ways. Before delving deeper, it becomes important to understand how the combination of the two technologies can serve as a potent tool for any business enterprise.
How These Technologies Make A Deadly Duo
Data has become extremely significant these days as a majority of businesses are data-driven. They rely on it in a variety of ways, from increasing their efficiency and reducing costs to delivering better customer experiences and formulating effective marketing strategies. AI is the technology that enhances the potency of data manifold and together, these two technologies pair as a deadly duo. With AI, businesses are empowered to store copious volumes of information and analyze them quickly and accurately for reliable insights. Together, they have transformed the way the business-related information is collected and used by the businesses to their advantage.
How Big Data Has Transformed Artificial Intelligence
AI is a relatively older technology as it has been there for several decades now. However, it had not been able to yield tangible results because of the absence of datasets of sufficient size. The advent of Big Data has brought a transformational change by enabling interconnected machines to access voluminous databases, discard the redundant and useless parts of the datasets, get reliable insights from the remnant useful datasets, and use them for self-learning in a programmed manner. The incessant growth of the data size makes it more meaningful and contextually relevant for the AI-powered machines to improve their working with analytics. Let’s consider the example of the use of these technologies in customer care. With the right data made available at the right time, the AI-programmed customer care can proactively address the real-time as well as specific queries of each customer in the business database. In this way, AI can take the standards of customer care to the next level if powered by the right kind of information when it is needed.
How AI has improved Big Data
As it has been stated before, these technologies are mutually beneficial. While adoption of Big Data technology has opened a whole new world of opportunities for AI and machine learning, things work the other way round too. To begin with, Artificial Intelligence prevents redundancy by sorting and sifting the datasets with speed and accuracy to discard all the useless elements. It assists human beings in analyzing the data and identifying patterns automatically and accurately so that they can make informed business decisions. Not only does it make decision-making faster and more efficient, but also ensures that it is totally unbiased (something that usually happens when there is human involvement in the process).