Enhancing Business Intelligence: Harnessing Text Analytics, AI, and ERP for Data-Driven Decision Making

EasyChair Preprint 12746

Abstract

In today's data-rich business environment, the ability to extract valuable insights from vast amounts of textual and structured data is paramount for informed decision-making. This paper explores the integration of text analytics, artificial intelligence (AI), and Enterprise Resource Planning (ERP) systems to enhance business intelligence (BI) capabilities. Leveraging advanced text analytics techniques, organizations can extract meaningful information from unstructured textual data sources such as emails, customer feedback, social media, and documents. AI-powered algorithms further facilitate the analysis of this data, identifying patterns, trends, and sentiments that can inform strategic decision-making processes. Integration with ERP systems enables seamless data exchange and consolidation, providing a holistic view of the organization's operations. By harnessing these technologies synergistically, businesses can unlock valuable insights, optimize processes, mitigate risks, and drive innovation. This paper discusses the benefits, challenges, and best practices associated with implementing text analytics and AI within ERP environments, offering practical recommendations for organizations seeking to enhance their BI capabilities.

Keyphrases: Artificial Intelligence, Business Intelligence, ERP, Sentiment Analysis, Text Analytics, data-driven decision making, unstructured data

@booklet{EasyChair:12746,
  author    = {Mr Juli},
  title     = {Enhancing Business Intelligence: Harnessing Text Analytics, AI, and ERP for Data-Driven Decision Making},
  howpublished = {EasyChair Preprint 12746},
  year      = {EasyChair, 2024}}