As the era of big data continues to evolve, the need for efficient and effective query processing in big data analytics has become paramount. Traditional query processing methods often struggle to cope with the sheer volume, velocity, and variety of data generated in today’s data-driven world. To address these challenges, machine learning techniques have emerged as a promising avenue to enhance query processing in big data analytics. This abstract provides an overview of the key trends in utilizing machine learning for query processing in the realm of big data analytics. It explores the various ways in which machine learning is transforming the field, from query optimization and performance enhancement to natural language query understanding and automated data discovery. The trends discussed in this abstract include: Query Optimization, Predictive Analytics, Natural Language Processing (NLP), Automated Data Discovery, and Data Quality Improvement, This abstract highlights the growing importance of machine learning in the domain of big data analytics and offers insights into how these trends are shaping the future of query processing. Machine learning is a driving force behind the evolution of big data analytics, enabling organizations to extract meaningful insights and value from their vast data repositories.
Keywords: Automated Data Discovery, Big Data Analytics Trends, Natural Language Processing (NLP), Predictive Analytics, Query Processing, machine learning, query optimization
