Deep Natural Language Processing in unstructured big data analysis and insights extraction - A quantitative study

Abstract

In today’s digital age, businesses create tremendous data as part of their regular operations. On legacy or cloud platforms, this data is stored mainly in structured, semi-structured, and unstructured formats, and most of the data kept in the cloud are amorphous, containing sensitive information. With the evolution of AI, organizations are using deep learning and natural language processing to extract the meaning of these big data through unstructured data analysis and insights (UDAI). This study aims to investigate the influence of these unstructured big data analyses and insights on the organization’s decision-making system (DMS), financial sustainability, customer lifetime value (CLV), and organization’s long-term growth prospects while encouraging a culture of self-service analytics. This study uses a validated survey instrument to collect the responses from Fortune-500 organizations to find the adaptability and influence of UDAI in current data-driven decision making and how it impacts organizational DMS, financial sustainability and CLV.