Role of Quantum Computing in a Data Analytics Environment

Abstract

There is a strong consensus that quantum computers are likely to solve previously intractable problems, especially in data science and AI. Nowadays, processing power of machine learning algorithms is limited by that of conventional computers. Quantum computing (QC) is one of the digital trends with the quickest rate of growth, and it seems to provide an answer to large data problems. It is a combination of the fields of computer science, information theory, and quantum physics. Quantum computers use the ability of subatomic particles to exist in more than one state at once to solve complex problems. In spite of its recent origin, quantum computing is already being used in the field of data analytics. QC can process huge datasets at much quicker rates and can provide data to AI models. By comparing schemas to swiftly assess and comprehend the link between two counterparts, QC can also aid in the integration of data. The ability to perform more sophisticated analysis and build machine learning models is a benefit of employing quantum computers.