Harnessing Unstructured Big Data using Machine Learning and NLP

Abstract

The exponential growth of unstructured data, encompassing text, audio, video, and images, has necessitated the development of advanced methodologies for effective analysis. Traditional data processing techniques often fall short in extracting meaningful insights from such data. This paper explores the integration of Machine Learning (ML) and Natural Language Processing (NLP) within cloud-based big data analytics frameworks to harness unstructured data effectively. We examine the synergy between these technologies, focusing on their application in various domains such as healthcare, social media analytics, and customer sentiment analysis. The study highlights the challenges encountered in processing unstructured data and presents solutions through the adoption of ML and NLP techniques. Furthermore, we discuss the scalability and efficiency achieved by leveraging cloud computing resources in handling large volumes of unstructured data. The findings underscore the transformative potential of combining ML, NLP, and cloud computing in unlocking insights from unstructured data, thereby facilitating data-driven decision-making processes across industries.