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"analysts" - lol! I know a HR director at a multi-national. He'd had enough of Excel and liked the look of this Python thing. I showed him R as well for bala
by gerdesj 6y ago
"analysts" - lol!
I know a HR director at a multi-national. He'd had enough of Excel and liked the look of this Python thing. I showed him R as well for balance but he wanted Python. I showed him how to install a Python distro and MS Code on his Windows machine, wired them up and off he went a few months back.
The board are in awe of his presentations. He is not an IT bod at all but a Uni. degree in Psycho. involves a fair amount of stats so a fair grounding there. He grabs huge data dumps from payroll etc and performs analyses that are complex but just work.
I think one of the benefits of using Python is that you instantly divorce input data, calcs and reporting. Fire up Excel and the first thing you often do is write a title. Using Excel properly requires a lot of discipline - I wrote a Finite Capacity Planner, with forecast and labour planner for a pie factory in Excel with quite a lot of VBA. It ran my P60 hard but did the job iteratively in about 2 to 5 minutes. Easter and Chrimbo needed a fair bit of tweaking by a Planner but most of the time my model told several supermarkets what they would be ordering back in the mid 1990s and they mostly faxed or EDId our forecast back as an order.
My brother (cough) is absolutely not an analyst in the normal sense. That a non programmer can bolt together enough Python to perform analyses useful to his job is testament to the power of the libraries and examples and documentation available. I've seen his code: suck in data, process it, spit out results, report results. That's all he needs and not a OO abstraction in sight.
My two examples (me and my FC Planner with Excel and an HR bod thrashing some data to a report with Python) are different things and each uses the opposite "tool for the job" discussed in the OP. However, it is how you use a tool that is important.
- klelatti 6y agoThanks for some great anecdotes! A couple of thoughts: - It's often not is Python a good fit for the task but are there Python libraries that are a good fit? If so the actual Python code may be pretty trivial and the equivalent Excel a lot more complex. - Writing good Excel is definitely possible but needs real discipline as you say - and bad Excel can be really bad!
- wendyshu 6y agoWhat's a bod?
- afavour 6y agoA “body”/a person. I suspect the OP is from the U.K. or Australia or similar, it’s slang there. I suppose it’s kind of a gender neutral version of the U.S. “guy”.
- deleted 6y ago[deleted]
- gerdesj 6y agoA "bod" is a person (body.) It is a colloquialism in the UK. You generally only use it in this case to denote an anonymous/generic person: "A bod did stuff". However, bod is also used as a formal abbreviation for body: "You have a lovely bod". In this case you should be reasonably familiar with the object or you will get slapped! Sorry, bod means a person.
- tomcam 6y agoAll good anecdotes, but I’m still kind of stuck on the whole you got to work at a pie factory thing
- gerdesj 6y ago(Sorry, misty eyed recollection alert) I should point out that "pies" in the UK is a rather generic term. MBOs (mince beef and onion), sausage rolls, pasties, pork pies and quiche was made in this south Devon based factory, near Plymouth. It was a good corp citizen thing to attend the 1100 "taste panel" which was part of the quality process. Obviously Product Dev, QA and the line crews could not mark their own work so office staff were expected to taste to standard. The idea is that you taste samples from the store that is post bake. This is a perishable product and there are stores (freezers, chills etc) to provide time buffers throughout production. There are a lot of constraints. You always make to forecast. In this case, back then, you had to deliver to depot with seven plus days of shelf life. The product needs meat and dough prep, make, bake and wrap and shoving in the back of a trunker (lorry/truck). You need to ensure you've got all your raw ingredients available and most of those have a shelf life and somewhere to store. Your machines have a nominal 100% production rate and a defined servicing period, expected breakdown rate, need cleaning and more. Some machines will do the job end to end and some will only do part of the process. You have bakeries and stores with varying characteristics. Some products have special requirements. It is clearly a "simple" job of defining, understanding and controlling your constraints and solving a few equations. I absolutely loved it as a challenge. This was 1995ish. I inherited a System 36 that was basically a glorified accounting system with some stock control and a few other things. If it got too warm in summer I used to put bags of solid CO2 that I could scrounge from Despatch (the whole factory panics when it gets really hot) in it. I am quite partial to pork pies and pasties.
- Foobar8568 6y agoAnd I have seen a board member not wanted anything but linear regression from his own data scientist team (If I remember well, they were like 5~ PHD or master in stats) because he couldn't understand anything. And that was in one of the largest organization in the world.
- nojito 6y agoData scientists are useless if they don’t have the right communication skills to empower decision makers. This is why linear regression will always be king and people who know how to turn complex problems into linear problems are worth millions.