Volume 9, Number 9, July 2019

Query Performance Optimization in Databases for Big Data

  Authors

Manoj Muniswamaiah, Tilak Agerwala and Charles Tappert, Pace University, USA

  Abstract

Organizations maintain different databases to store and process big data which is huge in volume and have different data models. Querying and analysing big data for insight is critical for business. The data warehouses built should be able to meet the ever growing demand of data. With new requirements it is important to have near real times response from the big data gathered. All the data cannot be fit in to one particular database “One Size Does Not Fit All” since data originating from sources have different formats. The main focus of our research is to find an adequate solution using optimized data created by data engineers to improve the performance of query execution in a big data ecosystem.

  Keywords

Databases, Big data, Optimization, Analytical Query, Data Analysts and Data Scientists.

Conference Proceedings