why is cloud computing essential for day
to science did you know that US retail
giant wal-mart generates 2.5 petabytes
of data from approximately 1 million
customers every hour and in case you're
wondering how much is a petabyte as I
did when I first read this it is equal
to 1 million gigabytes the equivalent of
13.3 years of HD video considering that
Walmart locations are open for business
for more than 10 hours a day we get a
staggering 130 years of HD video and 25
petabytes of data collected on a daily
basis yes
there aren't many companies like Walmart
but even smaller enterprise nowadays
generate huge amounts of data so it
becomes increasingly more challenging to
take advantage of such information
abundance and yes data science is at the
heart of all that but before we can
apply data science we must do justice to
another crucial player the cloud and
cloud computing in general that's
exactly what we will focus on in this
video
why cloud computing is essential for
data science in the 2020s but before we
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back to cloud computing to understand
the advantages cloud computing provides
when it comes to data science let's
imagine a world with as much data as we
have today but without servers in such
an unfortunate scenario firms would need
databases that run locally right so
every time when you as a data scientist
want to engage in new analyses or
refresh an existing algorithm
you'd have to transfer information to
your machine from the central database
and then proceed to operate locally this
unfortunate world would have several
main drawbacks manual intervention would
be necessary to retrieve data
machine becomes a single point of
failure for the analyses you have worked
on locally processing speed would be
equivalent to the computing power of
your computer chances are you will be
able to work with a limited amount of
data due to the limited computing
resources at your disposal moreover
under the setup you wouldn't be able to
leverage real-time data to build
recommender systems or any type of
machine learning algorithms that require
a live data doesn't sound like the
perfect scenario does it well that's why
we invented servers and then these
servers had drawbacks of their own the
most obvious one is that a server needs
space to be stored a cloud is basically
somebody else's server so their storage
problem server infrastructure is
expensive to buy and set up cloud
infrastructure is already there and is
simply awaiting your server consumption
in-house data storing requires you to
have backups and ideally have them in
different locations clouds offer data
everywhere anytime usually backed up on
many different servers across the world
servers need planning for fast growing
companies servers needs could be
unpredictable even for the current
quarter with in-house servers you
usually end up buying more servers than
you actually need at a given time with
cloud you pay as much as you use you see
my point right fortunately we now have
clouds may overshadow local servers in
almost every conceivable aspect and in
fact data scientists should be focused
on developing great algorithms testing
hypothesis taking advantage of all
available data without having to wait
hours to see the results of the test
they are performing and certainly
without having to worry how much memory
space they have left on their computer
and yes sometimes data scientists do end
up waiting for long hours for an
algorithm to train but with the cloud
they have the option to pay more and get
the job done faster that's yet another
advantage of cloud computing over
servers that being said the biggest
winners are smaller entities as they get
cheap access to the same tools as
enormous corporations and this is why
cloud technologies are a huge enabler
they create a level playing field and
allow small players to compete
with much bigger ones if you think about
it this technological progress changed a
number of businesses in a way similar to
how the internet changed Commerce
remember when all of a sudden people
around the world were able to open
ecommerce stores and compete on a global
scale with the established firms well in
the same way cloud technologies
democratized data analysis in data
science the fact that data scientists
and data analysts can rely on data
stored on the cloud truly makes their
life so much easier in addition most
cloud providers allow data scientists to
access readily installed open source
frameworks right away this is not only
super convenient but can also be a huge
time saver alternatively if you wanted
to use Apache spark in the conventional
way you would have to start by
installing Java then continue by
installing skaila after which you'll be
able to download Apache spark and
install it that's the setup you need to
go through if you are working on your
own PC however if you are using a cloud
service you'll be able to start working
with the Apache spark framework right
away yep
it's been already installed for you the
same is valid for many different open
source frameworks this type of easy to
access easy to use infrastructure is
very attractive and potentially applies
to all sorts of applications data
analysts and data scientists use in
their work over the last few years
Amazon Web Services Microsoft Azure and
Google cloud have tried to boost their
cloud services in terms of capability to
run machine learning algorithms the big
three of cloud services focused on this
area extensively as they realized it
could be an important source of
competitive advantage in the long run
and in case you're wondering
one of the biggest sell points of cloud
machine learning is that it allows small
and medium sized enterprises to access a
machine learning infrastructure they
otherwise wouldn't be able to afford for
example thanks to cloud-based machine
learning a small ecommerce retailer
could run a real-time recommender system
algorithm to improve the product
offerings shown to customers based on
the products they have already added to
their cart in this type of business
every website click can be interpreted
as a particular type of intention and
signa
and hence the real-time updated
algorithm operating in the cloud we'll
be able to make a suggestion that
improves the chances of making a
conversion in maximizing revenues
without cloud-based machine learning
setting up the necessary infrastructure
to perform this type of analysis would
be really costly and difficult to
execute for small and medium-sized
enterprises it is still unclear who will
win the cloud war between giants like
AWS Microsoft Azure and Google cloud but
one thing is certain this is a service
that benefits greatly small and
medium-sized businesses enabling them to
level the playing field when competing
against large multinationals with
superior IT infrastructure if you liked
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