Data analytics to derive actionable business intelligence

dc.contributor.advisor	Laha, Arnab Kumar
dc.contributor.author	Divya
dc.date.accessioned	2021-09-14T04:29:55Z
dc.date.available	2021-09-14T04:29:55Z
dc.date.issued	2019
dc.identifier.uri	http://hdl.handle.net/11718/24220
dc.description.abstract	In this project, data Analytics will be applied to assembly line operations of Bosch to predict which internal component is likely to fail (Bosch, 2016). This is a wide dataset and the dependent variable, failure of a part, is categorical. Similarly, in the case of Mercedes-Benz, the given dataset needs to analyzed to determine the time on the bench for various combinations of car features and testing protocols (Mercedez-Benz, 2017). Here, the parameters are categorical but the predicted time is a continuous quantity.	en_US
dc.language.iso	en	en_US
dc.publisher	Indian Institute of Management Ahmedabad	en_US
dc.subject	Data analytics	en_US
dc.subject	Business intelligence	en_US
dc.subject	R (Computer programming language)	en_US
dc.title	Data analytics to derive actionable business intelligence	en_US
dc.type	Student Project	en_US