Abstract: Business intelligence (BI) is crucial for informed decision-making, optimizing operations, and gaining a competitive edge. The rapid growth of unstructured text data has created a need for advanced text analysis techniques in BI. Natural language processing (NLP) is essential for analyzing unstructured textual data. This chapter covers foundational NLP techniques for text analysis, the role of text analysis in BI, and challenges and opportunities in this area. Real-world applications of NLP in BI demonstrate how organizations use NLP-driven text analysis to gain insights, improve customer experience, and anticipate market trends. Future directions and emerging trends, including multimodal learning, contextualized embeddings, conversational AI, explainable AI, federated learning, and knowledge graph integration, were explored. These advancements enhance the scalability, interpretability, and privacy of NLP-driven BI systems, enabling organizations to derive deeper insights and drive innovation in data-driven business landscapes.