Deepika Kapoor


Apparel retailers are increasingly turning to data analytics to keep up with the latest trends and consumer demands. To meet the demands of "fast fashion", businesses must also price items correctly, know when to reduce them, stock enough of the right styles, colors, fabrics and sizes, and make sure that stores can well be supplied and operate efficiently. Data analytics has long used in the retail industry to analyze sales information. However, new sources of data are now available for retailers to discover more about what customers might want is the use of cognitive computing programs that simulate human thought processes and mimic the functions of the brain. In the present study, we have used the concept of KDD i.e. Knowledge Discovery in Databases to predict future sales in apparel. This is done using data mining methods (algorithms) to extract (identify) what is deemed knowledge, according to the specifications of measures and thresholds, using a database along with the required preprocessing, sub-sampling, and transformations of the database.

Keywords: Apparel-retail, Data analytics, Knowledge Discovery in Databases (KDD), Data mining.

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