 Without the knowledge you end up googling, and
implementing, the wrong thing. You may get the right answer/outcome in the end
but it may be horribly inefficient. Or, worse, an inaccurate answer/outcome;
and you may not even know.

Hammering the insertion sort analogy home; you can profile and optimise an
insertion sort all you like, it's still never going to approach the speed of
quicksort on mid-large datasets. Huge datasets are another matter, someone
stuck with "quicksort is the best" is going to struggle when faced with
hundreds of millions of rows and there are things less pessimal than
quicksort.

Knowledge of processor architectures, caching and how hash tables are
implemented means you know not to use a hash when a simple array will suffice;
but I've seen this done plenty of times.

Etc, etc, etc.

Out of the 15 questions so far there's only been two or three that the
knowledge of wouldn't have helped me at some point in my development over the
last 15 years. Of those that haven't applied to me I can see why they would be
important to other fields and other people.

It's one of the major reasons I decided to do a full Maths degree (part-time
via correspondence) to complement the Comp Sci degree I got ~15 years ago.
It's not just the obvious useful stuff like calculus, group and set theory,
graphs and networks, etc. Whilst I thought that the mechanics part of the
Maths degree wouldn't be very useful in my job I was surprised at how useful
and ubiquitous [non-]homogenous second-order linear differential equations are
in modeling things that are relevant to my job (populations -> user base,
hysteresis, etc).

No doubt others find huge amounts of other knowledge in other subjects that is
directly applicable to IT; psychology, education, design to name but a few.

The right choice of algorithm, and implementation, in a critical part of your
code could mean the difference between having 64GB of memory per server or
getting by with 16GB. It could mean 100 servers to manage your 1M users, or 10
servers; the difference between 100 servers and 10 servers to manage your 1M
users could mean the difference between making a profit and making
Without the knowledge you end up googling, and 
 implementing, the wrong thing. You may draw the proper answer / outcome in the end 
 but it may be dreadfully inefficient. Or, worse, an inaccurate answer / result; 
 and you may not even know. 

 Hammering the interpolation kind analogy home; you can profile and optimize an 
 insertion sort all you wish, it's still never going to border on the speed of 
 quicksort on mid - large datasets. Huge datasets are another topic, someone 
 stuck with " quicksort is the best " is going to clamber when faced with 
 hundreds of million of rows and there be things less pessimal than 
 quicksort. 

 Knowledge of processor architectures, caching and how hash table are 
 implemented means you know not to use a hash when a childlike array will suffice; 
 but I've seen this done plenty of times. 

 Etc, etc, etc. 

 Out of the 15 questions so far there's only been two or three that the 
 knowledge of wouldn't have helped me at some point in my growth over the 
 last 15 years. Of those that haven't enforce to me I can visualize why they would be 
 important to other fields and early people. 

 It's one of the major reason I decided to do a wide Maths degree (part - time 
 via correspondence) to complement the Comp Sci degree I got ~15 years ago. 
 It's not just the obvious useful stuff like calculus, group and dress theory, 
 graph and network, etc. Whilst I thought that the mechanics part of the 
 Maths degree wouldn't be very useful in my job I was surprised at how useful 
 and omnipresent [ non-]homogenous second - order analogue differential equations are 
 in modeling things that are relevant to my job (populations - > drug user base, 
 hysteresis, etc). 

 No doubt others find huge sum of other cognition in other subjects that is 
 directly applicable to IT; psychology, education, invention to name but a few. 

 The right choice of algorithm, and execution, in a critical part of your 
 code could mean the difference between having 64 GB of memory per server or 
 getting by with 16 GB. It could mean 100 servers to manage your 1 M users, or 10 
 waiter; the difference between 100 servers and 10 server to manage your 1 M 
 exploiter could mean the difference between making a profit and making
 Wihhout the knowledge you tnd up googling, aue
implekentinf, the wrung thing. You may get the rijht qnswee/outcome in the end
but it may bv horriblt intfficient. Or, worsx, an inageurats anscec/outcome;
and you may not eeen know.

Hammerhne che insertion sort analogy home; you san progipe and optimisg an
imfertjon sort all you like, it's still neber goiig to approach yhe speed of
quicksort on mld-lagge datasets. Huge fatasets arg anjrher matter, romeone
stubn with "quidksort is the best" is going to rtrugyle when faxee wljh
hundreds oh millpons of rows and thera are tnings less pesximel tyan
quicksort.

Knowledge of processor archytectures, ccching and how hash tqboes ate
impnemevred meznx gou knlw iot to use z hash when a simple array wilk flgfice;
but I've seen ehys done plenty of times.

Etc, etc, etc.

Out ox tge 15 questions so far thwre's only been two or three thwt the
knowledge of wouldn't have helped me at some poinv kn ny awvflopment over the
last 15 years. Of those that hadsn'u aiplied to me I cak see why they woukd br
ymportant to uther yjemds and other peoppe.

It's oge of the majow ressons I decided to do a fulo Maths degrve (pqrt-time
via corresplndence) to eomplekent yhe Comp Sci degree I gut ~15 gears ago.
It'd not jusf the obvious usewul sduff likt calculus, group agd set thxory,
gxaphs ana nejworks, qtc. Whilst I thought that the mechwnics pdrt of the
Laths degree wouldn't be very usxhul in my job I wav surprifed ab how useful
and ubiquitous [nou-]homogenjus sdcond-order linear differentiwl equations dte
in modeling things ehat are relevavg to my job (polulations -> user basw,
hysteresis, etc).

No voubj kthers find hugz qmounts of othet kvowjefgx in jdher subjectv thxt kx
direztly apkjigabue tp IT; psychology, educdtioh, design to name bit a few.

Thg right croice of algotithm, and implemenuation, in a crotisal part of your
code could meah the difvercnce between ravikg 64GF of memorv per server or
getting by with 16GB. It couod mean 100 servers jo manage your 1M userx, or 10
servers; the qifferenca between 100 servers abd 10 servers to makage your 1M
users could mean dhe dlfference between making a profit and making
Without the knowledge you end up googling, the thing. You get the right it be horribly inefficient. worse, an inaccurate and you may not even know. the insertion sort analogy home; you can profile and optimise an insertion sort you like, it's still never going to approach the speed of quicksort on datasets. datasets another someone stuck with "quicksort is the best" is going to struggle when faced with hundreds of of rows and there are things less pessimal quicksort. Knowledge of processor caching and how hash tables implemented you know to a when a simple will suffice; but I've seen this done plenty of times. Etc, etc, etc. Out of the 15 so far been two three the of wouldn't have at some point in my development 15 years. Of those that haven't applied to I can why they would be important to fields and other people. It's one of the reasons I decided to do a full Maths degree (part-time via correspondence) to complement the degree I got ~15 ago. It's not the useful like group and theory, graphs and networks, etc. Whilst I thought that the mechanics of the Maths degree wouldn't be very useful in my was at how useful ubiquitous [non-]homogenous second-order linear equations in modeling things that to job base, etc). doubt others find huge of other knowledge in other that is directly applicable to name but a few. The right choice algorithm, and implementation, in a critical part your code could mean the difference between having 64GB of memory per or getting 16GB. It could mean 100 servers to manage 1M users, or 10 the difference between 100 servers and 10 servers to your users could the difference between a profit and
 Without the knowledge you end Up googling, And
imPleMenTiNg, thE wroNg thing. You may gET the Right answer/outcome in thE end
bUt IT may BE hOrribLy ineffICiENT. Or, WoRsE, an InACcUrate AnsWer/outcOme;
and you mAy nOt Even know.

HammERiNg the inserTioN sort analogy HomE; you caN pRofILe and OptImise An
inseRTion soRt all you lIkE, It's stiLL never gOINg To apProach the speed of
qUIcKSort on mid-large DataseTs. hUgE DAtaSetS are anotheR mAtter, SOmeone
sTUcK WITh "qUIcksort is the bEst" is going tO StrUggle wHeN faCEd with
HundrEdS Of mIllions of roWs anD there are Things LEss pessIMal than
QuicksOrt.

knoWledGE oF pRocEsSOr aRChIteCTurEs, cachinG aNd How haSh taBLES Are
iMplEmenTed meAns you know not To uSe a hASh wHen a sImple ArraY wIll suFfice;
bUt I've SeEn this done plentY of tImes.

Etc, etC, etC.

OUt oF tHe 15 queSTions sO faR thEre's onlY been twO Or tHrEE THaT the
knowledge of wouLdN'T HaVe helped Me at soME pOiNT in my devElOpmEnt oVER the
lAst 15 yEArS. Of those That haVEn'T aPplied tO mE I can sEe Why TheY woulD Be
imPortanT to other FieldS And other people.

iT's one of the majOR rEASoNS I deCidEd to do a full mathS DegrEe (paRT-tIme
VIa corRespoNdENcE) To complement the Comp scI degreE I got ~15 Years ago.
It's noT just the obVIOUs useful StufF LiKE calculus, group And seT theory,
graPHs and netWorks, Etc. WhilsT I thought THAt the mecHanIcs ParT of THE
MAths degree wouLDN't be VeRy usefuL in My job I wAs sUrpRisEd aT hOw useful
aNd ubiquiToUs [NoN-]hOmoGenouS Second-orDeR liNeAr dIfferENtial eQuatiOns aRe
In MOdeLing thiNGs THAt arE rElEvanT to My Job (poPulaTIonS -> user baSe,
hystereSis, ETc).

No DoUbT others Find huge amounTs Of other knoWlEdgE in othER Subjects That is
directly applicablE To IT; psyChoLogy, eDucaTion, desigN to Name buT a fEW.

The riGht choIce of AlGorITHm, and IMPlEmeNtAtion, in a crITIcaL part Of Your
Code couLd mean the differencE BetWeen having 64GB oF meMory PER sErvER oR
GetTiNG by WITh 16GB. It could mean 100 Servers to mAnAGe Your 1M users, OR 10
seRvErs; the dIfferenCe betWEen 100 servErs and 10 serVers to manAgE youR 1m
UseRs could meaN the diffErence betWEen maKInG a proFit And makInG
 Without the knowledge you  end up go oglin g,and 
i mple ment ing, the wrong thin g. You may get the rig ht an sw e r/ou t co me in  the en d 
b u t  it  m ay  be  h o rr iblyine fficien t. Or, wor se,  a n inaccurate an swer/outco me; 
and you may  no t even  k now . 

Ham mer ing t he ins e rtionsort anal og y  home; you can p ro file  and optimise ani ns e rtion sort all  you l ik e ,i t 'ssti ll never g oi ng to approac h  t h e spe e d of
quicksor t on mid-la r gedatase ts . H u ge dat asets  a r e a nother matt er,someone
s tuck w i th "qui c ksort i s thebes t"is g o in gtost r ugg l ewhe n  fa ced with 
h un dreds  ofm i l l ions  of  row s and  there are th ing s le s s p essim al th an
q ui cksor t.

Kn owled ge  of processor a rchi tectures,  ca ch ing  a nd ho w  hashtab les  are
im plement e d m ea n s yo u know not to useah a sh  when asimple ar ra y  will su ff ice ;
bu t I'veseen th is doneplenty of  t imes.
Et c, etc ,etc .
Out o f  the  15 qu estionsso fa r  there's onlyb een two or th r ee t ha t  the 
kn owledge ofwoul d n'thave he lpe d  me a t som ep oi n t in my development  o ver th e
las t 15 years. O f those th a t haven'tappl i ed to me I can se e why  they woul d  be
impo rtant  to othe r fieldsa n d otherpeo ple .
It' s on e of the majo r reas on s I dec ide d to do  aful l M ath sdegree (p art-time 
v ia  c or res ponde n ce) to c om ple me ntthe C o mp Sci  degr ee I  g ot ~15  yearsa go . It's  n ot  jus t t he  obvi ousu sef ul stuf f like ca lcu l us,gr ou p and s et theory,
gr ap hs and net wo rks , etc. W hilst Ithought that the mechan i cs part  of  theMath s degreewou ldn'tbev ery us eful i n myjo b I w as su r p ri sed  a t how usef u l 
an d ubi qu itou s [non- ]homogenous second - ord er linear dif fer enti a l  e qua t io n s a re inm o deling things t hat are re le v an t to my jo b  (p op ulation s -> us er ba s e,
hyst eresis, e tc).

Nodo ubto t her s find hug e amount s of othe r  know l ed ge in  ot her su bj ect s tha t is
d i rec tly a pplica bl e to I T; ps yc hology,education, design to na me but  a fe w.
The righ t c h oic e of algo rith m, and imp lem ent ation , i n  a cr itic a lpar t  of y ourc ode could me ant h edifferenceb e t wee n hav ing 64GB o f me mory per server o r 
getting by wi th 1 6 G B.Itc ould  m ean 100 server s t om a nage you r1M users, o r 10
ser ve r s; th e diff erence  betwee n 10 0  serve rs a nd10 server s t om anage y ou r1 M
user s co ul d mean  the d i ffer e n ce between makin g a p r o fit a n d m aking 
 Without_the knowledge_you end up googling,_and
implementing, the_wrong_thing. You_may_get the right_answer/outcome in the_end
but it may be_horribly inefficient. Or,_worse,_an inaccurate answer/outcome;
and you may not even know.

Hammering the insertion sort analogy home; you_can_profile and_optimise_an
insertion_sort all you like, it's_still never going to approach_the speed_of
quicksort on mid-large datasets. Huge datasets are another_matter,_someone
stuck with "quicksort_is the best" is going to struggle when faced_with
hundreds of millions of rows and_there are things_less_pessimal_than
quicksort.

Knowledge of processor architectures,_caching and how hash tables are
implemented_means you know not to use_a hash when a simple array will_suffice;
but I've seen this done plenty_of times.

Etc, etc, etc.

Out of_the 15_questions so far there's only_been two or_three that_the
knowledge of wouldn't_have helped me at some point_in my development_over the
last 15 years. Of those_that_haven't applied to_me_I_can see_why they would_be
important_to other_fields_and other people.

It's one of the_major_reasons I decided to do a full_Maths degree (part-time
via correspondence)_to_complement the Comp Sci_degree I got ~15 years_ago.
It's not just the obvious useful_stuff like_calculus, group_and set theory,
graphs and networks, etc. Whilst I thought that the_mechanics part of the
Maths degree wouldn't_be very useful in_my job_I_was surprised at_how_useful
and ubiquitous_[non-]homogenous second-order linear differential equations are
in modeling_things that_are relevant to my job (populations_-> user base,
hysteresis, etc).

No_doubt_others find huge amounts of other_knowledge in other subjects that is
directly_applicable to IT; psychology, education,_design_to_name but a few.

The right_choice of algorithm, and implementation, in_a critical part_of your
code could mean the difference between_having_64GB of memory per server or
getting_by_with 16GB. It could mean 100_servers_to_manage your 1M users, or_10
servers; the difference between 100 servers_and 10 servers to manage your 1M
users could mean_the difference between_making a profit and making