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Data Science analysis

A laptop manufacturer deals with services to customers after they purchase a product. This means they deal with data regarding tech support, warranties, repairs, etc. For this assessment, I am interested in seeing some data skills and thought process around making sense of this kind of data.

In the work sample, please make sure to comment the work. I am most interested in seeing the thought process, not just the code that is written.

In addition to submitting the work sample exploring this dataset, please write down interesting questions you think could be answered with this data.

Data Definitions

Asst_id – an identifier for each individual machine sold

Product_type – class of product that describes the asset

Region – region where the asset is located

Country – country where the asset is located

Mnfcture_wk – week when product was manufactured

Contract_st – week when warranty became active

Contract_end – week when warranty expires

Contact_wk – week when customer contacted laptop manufacturer

Contact_type – way that customer contacted the laptop manufacturer

Issue_type – type of problem identified by customer

Topic_category – type of problem as classified by the tech support agent

Parts_sent – what parts were sent to fix the problem

Repair_type – if a part was required, this is a hard repair; otherwise, a soft repair

Repeat_ct – how many additional visits were required to fix the problem, past the first one

Parts_ct – how many parts were sent to fix the problem

Agent_tenure_indays – how long the tech support agent has worked in the manufacturer’s tech support

Contact_manager_flg – did the tech support agent have to bring in a manager to solve the problem

Diagnostics – were agents compliant with diagnostic usage

Repeat_parts_sent – which parts were sent on additional visit

Навыки: Анализ и обработка данных, Machine Learning (ML)

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( 0 отзыв(-а, -ов) ) Seattle, United States

ID проекта: #30917962

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