IIMA Institutional Repository
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Please use this identifier to cite or link to this item:
http://hdl.handle.net/11718/24220Full metadata record
| DC Field | Value | Language |
|---|---|---|
| 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 |
| Appears in Collections: | Student Projects | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| SP_2654.pdf Restricted Access | 1.44 MB | Adobe PDF | View/Open Request a copy |
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