Here is Part 2 of my talk with an old friend turned Data Scientist. You can find Part 1 here. In typical fashion he comes right out with the straight dirt. Without knowing it he got right to the point of a problem I was having. Would Data Science or Business Intelligence be the best path to take? This conversation was a turning point for me. It clarified a couple of important (vital) points and also gave me perspective on what the market and industry are like.
Note: Once again I kept the editing minimal and only changed the order of a few posts to improve readability. Names and what not were changed to protect the innocent… although RocketMan’s innocence may be up for questioning considering his association with the likes of me.
Bolding is mine.
K: Hey man, got to thinking about this yesterday. Please do not be offended by what I'm about to say. I was thinking about your career pivot and would highly recommend against the data science/analyst route. I think you should pursue the business analyst/BI route, which will emphasize more sql, tableau, SAS, very basic stats. Coursera has some great series on the subject my wife recently took. From a DS perspective I checked your linkedin and you just don't have the academic/hard skills background that is table stakes. From there there is no experience in applying anything related plus age is working against you. For every one of you there are 20 of me who are younger, trained in various applied statistical modeling methods, and have experience applying these skills at a very high level. I'm just thinking from a practical perspective it will be very frustrating since the JHU course even combined with your intelligence (and know that i will always respect you) isn't going to necessary make up for this
Z: i appreciate your honesty. There is a reason i reach out to people that i know when i look into these things.
What course did she go through?
K: https://www.coursera.org/specializations/excel-mysql
i'd build out the sql more
Z: you have also potentially saved me a lot of heartache and headache from trying to crash through the side of a building instead of going in the front door.
K: i mean right now if you can't tell me when to apply a logistic vs linear regression model without looking it up, that's a big concern and dorks like me have had to do this for years. but you have the sales, people, and business side, which honestly will be longer lasting once the ds trend dies down. gartner already has it sliding down its hypecycle
Z: good to know, and again thank you.
K: tableau isn't the sexiest, but it's the most popular BI tool at the moment. maybe doing a course in R that uses some of the packages. datacamp i s great for that they have a few courses that i think kick ass vs JHU
and then read statistics for dummies, SQL or postgres for dummies, you'll be set
Their courses are fast, cheap, to the point
and in the r packages you would use on the job as a BI if you ever used r, which you likely won't
since most companies never run r in production
Z: they (Datacamp) look to be almost exclusively R
K: yup, a bit of python, but their r courses are the most directly useful i've found
they skip the fluff of the base functions you'll never use or need to know
you would need to know and use them if that's all you worked in developing models, but chances are you won't do that
plus, a good DS or BA will always start with the most basic tool first. if my dataset isn't over 1mil rows, i use excel before anything
or i'll do everything in sql, then excel. r for modeling, plotting, further exploration. sometimes an R extension such as Plotly.
Z: right on. BA/BI is much more in line with what i am interested in. actionable analysis, if you will.
K: so word of advice, don't use that term professionally
it's one of those things people say that has zero real meaning
Z: point taken.
fall over from accounting
K: oh man from govt work i have so many similar terms
'capacity building'
like, wtf does that actually mean
Z: duh... building capacity...
cuz reversing the words isn't just the equivalent of saying it louder
K: haha
another bad one is 'finding insights'
we used to have a buzzword dictionary at my old company of things to pepper proposals and reports with
"actionable research"
Z: that is hilarious
so in BA/BI still suggest scraping with python?
K: so my wife took that course you sent. i looked at her syllabi and assignments and thought that it was honestly pretty good for an applied course. mainly in that it did not add complexity she wont use in her analyst role
Z: the data warehousing?
K: this course: https://www.coursera.org/specializations/excel-mysql
K: oh the book 'automate the boring stuff' is great!
Z: adding it to my amazon list
Z: ran across that the other day
K: DS is almost an annoying title at the moment
the underlying definition seems to have been diluted significantly
i mean, before 2011 the term didn't really exist. literally. it was googled under 1000 times
ha ha
the best definition i've heard is that "Data Science is statistics done on a Mac"
Z: heard a data scientist was a data analyst that lives in San Fran
K: a statistics student that can use the adobe creative suite
Z: nice
stats + pretty graphics
K: they gave me the title at work and i took it bc median salary is higher for that than 'data analyst'
LOL
i proposed 'dungeonmaster of data'
Z: data overlord?
K: oracle of awesome
Z: nice
K: we should've just been rocket scientists like RocketMan
always going to need rockets
Z: speaking of which he says hello
K: oh i was gonna ask how he's doing
quick indeed search says BI pays well
not as well as DS, but still pretty good if you get the right gig
i really lucked out
they thought i was much better than i was and i did a lot of learning on the job
Z: finding a lot in the 70-80 range
K: sounds about right for entry level analysts
add PM to that and get a bump
Z: quick requirements scan makes it look like i need to learn to use SAP products
K: eh, yes and no
Z: expand pls
K: SAP BI tools are &@^#$%*!
oracle and MS the hitters
Hana is expensive, about to be outdated. the DBs use basic nosql or sql interfaces
the thing is you need to know the querying language. from there it's easy
so like we use oracle, which uses plsql for most stuff
aka sql with like 3 extra commands
Z: ha ha
MS is T-SQL i believe
K: yah it's all essentially the same
SAP has some map reduce stuff, but it's the same as any other mapreduce language
Z: which version of oracle are you guys using?
K: couldnt even tell you.
i usually use a local DB on my computer
and then do major operations through a proprietary tool that uses GPU mapping to vectorize functions
if you wanna make sick money
go learn cobol and work for a bank
it's the oldest, most boring language. but most needed right now
Z: ha ha ha i know some people that do that.
K: dude, they're all retiring!
and young guns don't learn that shit
my buddy got a job for B of A as a cobol developer for $195k starting. granted he is an awesome CS masters student, but still
FAA, SEC, IRS, basically everything in government and finance is all still cobol main frames. healthcare too
Z: ha ha nice. i can't remember the language but i once had to unearth a guy who could write in the previous embedded language and confirm against C++
jovial
new code quit being developed in the late 60s early 70s
helicopter control systems
guy made 80+ an hour
K: that's it?
that's pretty low for something that proprietary
Z: military contract
K: ah gotcha
Z: rural tx
K: makes sense
i miss billing hourly sometimes just to get an idea of what my time was worth
yah govt work is the worst. never fun, always pays atrocious wages
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