Volume 11, Number 5
Query Optimization for Big Data Analytics
Manoj Muniswamaiah, Tilak Agerwala and Charles Tappert, Pace University, USA
Organizations adopt different databases for big data which is huge in volume and have different data models. Querying big data is challenging yet crucial for any business. The data warehouses traditionally built with On-line Transaction Processing (OLTP) centric technologies must be modernized to scale to the ever-growing demand of data. With rapid change in requirements it is important to have near real time response from the big data gathered so that business decisions needed to address new challenges can be made in a timely manner. The main focus of our research is to improve the performance of query execution for big data.
Databases, Big data, Optimization, Analytical Query, Data Analysts and Data Scientists