Data Science analysis
Budget: $10 – $30 USD
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
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