Quantum Data Science: Using Quantum Computing for Database Management

Location

SU-217

Department

Computer Science

Abstract

Data science (DS) is a major field of study which identifies and uses modular information called data to do analyses, maintenance, and provide outcomes to those using it. Through DS, society is impacted in almost all domains, which plays an important role in respect to studying, analyzing, and collecting knowledge. With DS the world literally goes around, yet there are limitations to how we can process and compute data. As data warehousing and big data research increases in size and complexity, through traditional forms of computation there are growing signs of the supply not meeting conventional demands. A new field in science using quantum physics aims to efficiently process and maintain all data. It starts with quantum entanglement, superpositions, and quantum logic processing. Through this new form of computation, Quantum Technology (QT) would vastly change the way we look and handle data. Infusing DS and quantum computers would create a new field of study and research called Quantum Data Science (QDS). To create technology and software we need to understand what QDS and QT are, how they work, and what is needed to evolve the data landscape. Once defined, Quantum Database Management Systems (QDBMS) will help to expand the capabilities of data management that current conventions cannot. This new technology to utilize quantum computing is still in its infant phase. For this reason, there is a gap in literature on how we can define and construct the software, process models, and limitations to overcome before defining QT, QDBMS, and QDS. In this literature review we will survey the different techniques and methodologies with respect to data storage, data representation/schemas, and data management in both traditional computing domain and the futuristic quantum computing domain. This literature review will present the promising technology of quantum computing and what this new field of research can bring to the career domains and the impact it can provide for data engineers, software engineers, and data analysts.

Faculty Sponsor

Ahmed Khaled

This document is currently not available here.

Share

COinS
 
Apr 26th, 12:30 PM

Quantum Data Science: Using Quantum Computing for Database Management

SU-217

Data science (DS) is a major field of study which identifies and uses modular information called data to do analyses, maintenance, and provide outcomes to those using it. Through DS, society is impacted in almost all domains, which plays an important role in respect to studying, analyzing, and collecting knowledge. With DS the world literally goes around, yet there are limitations to how we can process and compute data. As data warehousing and big data research increases in size and complexity, through traditional forms of computation there are growing signs of the supply not meeting conventional demands. A new field in science using quantum physics aims to efficiently process and maintain all data. It starts with quantum entanglement, superpositions, and quantum logic processing. Through this new form of computation, Quantum Technology (QT) would vastly change the way we look and handle data. Infusing DS and quantum computers would create a new field of study and research called Quantum Data Science (QDS). To create technology and software we need to understand what QDS and QT are, how they work, and what is needed to evolve the data landscape. Once defined, Quantum Database Management Systems (QDBMS) will help to expand the capabilities of data management that current conventions cannot. This new technology to utilize quantum computing is still in its infant phase. For this reason, there is a gap in literature on how we can define and construct the software, process models, and limitations to overcome before defining QT, QDBMS, and QDS. In this literature review we will survey the different techniques and methodologies with respect to data storage, data representation/schemas, and data management in both traditional computing domain and the futuristic quantum computing domain. This literature review will present the promising technology of quantum computing and what this new field of research can bring to the career domains and the impact it can provide for data engineers, software engineers, and data analysts.