I work in quality department of some manufactory that produce different kind of property's/apartment's accessories. Located in quality of data analysis subsection. Prefer to not reveal what exactly (will later if needed) is being produced, although at the end of reading my post you would probably know what accessories they are. In reality always can go something wrong. No matter what kind of environment we work in. My project contains the case when whichever kind of problem occurs on client end location (property/apartment). Clients might be end users or resellers if some intermediate locations exist. For that project this isn't revelant but relevant is that the project includes situations when/where accessories are already physically on locations where they should operate. This is most likely user's living place. I plan to analyze within my project only situations when users contact repairmans to physically come to the doorstep, visit them, and fix the problem that occured on our manufactured accessories. Users might recognize this problem either by failure or by its consequence – it depends what failure is and what situation it is. Most of times by its consequence unless if failure is, e.g. noise (which happens very rarely, we all know noise is consequence of something going wrong). Such failure is recognized (heard) by users. But usually consequence is the red alert which causes user to contact repairman. How contact is being done doesn't matter. The only important fact is that user contacts repairman. Entire project is based on this assumption. If user tries to fix the problem on his or her or their own and even successfully, this does NOT count in the project. I don't even want to know this, it has zero meaning. Only situations I include are that users contact repairmans when something is wrong AND (!) that repairmen come to visit them with purpose to fix the problem. Just those two conditions matter. It doesn't matter if repairman comes within the deadline set by user, neither if repairman successfully fixes (usually they do) the problem on their first visit of user's living place already. Also it is completely irrelevant (but in analysis I might need to include such info too) when user contacts repairman. Problems for sure have priority than others: e.g. failures related to accessory' functionalities usually have priority than failures related to exterior shape/looking. Everything is in the database and I see all info/data. I analyse it in Excel, although I might need to work with data inside some other software such as mysql. I know data from Business Warehouse (excel's addon) can be transfered there from excel but I don't know much about mysql. Currently I work with few hundreds filters (I list few on request) and few thousands of conditions/parameters in those filters. I do NOT need to care about way how data is being filled into database, who exactly is filling it, neither whether or not something is missed. Just using data.
***So what Im trying to do: We have different manufactory departments. Each for its own type of accessories. Several types are being produced in our company. WHAT I WANT TO HAVE IS possibility to be able to announce for the FUTURE how many visits by repairmen will happen in unit % with accuracy up to two decimal digits. Such factor is number of visits divided by number of accessories produced. This is equation. Announcements should be grouped based on manufactoring department and based on country where visit happens (where user calls repairman and repairman comes to user's home). Many graphs comparions would need to be done. A lot needs to be done, towards getting this method, on how particular graphs are performing and compare pieces of them with same or similar pieces of new graphs. I would like to know some tips/suggestion where/how would I need to start with trying to develop such complicated data analysis algorithm.
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