Collection Development Using Data Analytics

The study aims to revamp the collection development policy using data analytics techniques at IGDTUW, Delhi. the study used the circulation records from 2022 to 2024 and found 30,612 records of library holdings. Further, 16,905 circulation records were also downloaded and used in data analysis. The library holdings data included book titles, authors, call numbers, and accession numbers. Furthermore, library-holding records and circulation datasets were loaded into Python. The Pandas library was used to read the Excel files. The study found that 23.05 % of books were heavily used, while 76.95 % remained unused. Interestingly, 30.7 % of faculty-recommended books were borrowed, showing a gap between faculty-recommended titles and student needs. The results helped develop a policy for selecting and removing books, ensuring the library’s collection is relevant, user-friendly, and space-efficient. This study provides a simple method other libraries can follow in collection development and better use their resources.