Augmented Analytics: From BI to Smart Analytics


Shivam Vora (student), Ayush Attawar (student), Parth Narechania (student), Dr. (Mrs.) Vinaya Sawant, Assistant Professor
Department of Information Technology, Dwarkadas J. Sanghvi College of Engineering, Mumbai, India.


Augmented analytics is an emerging field of data science that combines traditional data analysis techniques with artificial intelligence and machine learning to facilitate data-driven decision-making. Augmented analytics uses a combination of techniques to help organizations better understand, analyze, and gain insights from their data. By leveraging automated algorithms and natural language processing, augmented analytics enables organizations to identify patterns and trends quickly and accurately from their data, thereby allowing them to make more informed decisions. This paper will discuss the benefits of augmented analytics, the challenges associated with its implementation, and the technologies and frameworks used in its implementation. Additionally, this paper will explore current trends in augmented analytics and the potential for its use in future business operations. Finally, this paper will provide recommendations for organizations interested in using augmented analytics. By understanding the benefits, challenges, and implications of augmented analytics, organizations can better evaluate the potential of this technology to improve their operations.