Hello everyone this is Navjyotsinh
Jadeja and welcome to today's lecture
on what is data mining so basically
you've heard a lot about data mining and
machine learning in you know current
trends newspapers medium.com
and so many places but very few people
know what exactly is data mining so
into this lecture we'll be talking on
what is
data mining before that I'd like to tell
you that what are we going to discuss in
this lecture so in today's lecture we
are going to discuss on why data mining
because it's very important that we
understand what is the importance of it
why is it so and discuss why is it so
important and then we are talking on
what exactly is data mining then we're
moving further and finding out what data
mining is useful what are the
applications where can we use it and
then finally you know what kind of data
we need to mine we have said that is
also important that you need to
understand what different types of data
are available and how can we mine the
data and also it is important to
understand that all data can be mined
now this very important point we'll be
discussing and then finally major issues
in data mining so let's move further so
as I said why data mining so basically
we are drown with the data it's like
we're having so much of data and we're
not having knowledge and data mining is
basically a misnomer a lot of people
understand data mining in a very wrong
way
like if you're doing a gold mining if
you're doing coal mining and in those
cases you're actually digging it for the
gold whereas here you're not you know
mining for the data you mine for the
knowledge so the data mining is also
known as knowledge mining or knowledge
discovery in data mining and the reason
for data mining being so important is
this there is a huge amount of data
available and fact according to
statistics which I have been knowing and
studying is that amount of data which is
produced in the last two years is more
than the total amount of data produced
in earlier whole century so it's a huge
amount of data so where is this data
coming from this data is coming from
different platforms which you are
connected on like social media platforms
everyday all of you log in into social
media platforms like Facebook Instagram
Twitter etc and you've been posting so
many things you talk on things you like
you
you know you dislike you share everything
then there are ecommerce platforms which
I've taken a boom amazon ebay flipkart
etc where people go online sell
products check out the different you
know comparative analysis of the
different products and there is a whole
lot of you know data generated there
also along with that all governments are
getting online so there are a lot of
online records of your education the
Aadhar links the bank transactions and so
much more and also all you know there's
a whole variety of new thing that will
being generated from news blogs and
other media's so this overall means that
there's a huge amount of data available
now only concern is how we can utilize
this data to generate some sort of a
knowledge which can be used for decision
making so that is what we are talking in
data mining is it basically discovering
hidden patterns from already available
data data can be available in
different forms it can be hard copy it
can be soft copy it can be online
records it can be clicks on the media it
can be you know your keys in the browser
so much but if that can help us and find
out you know some patterns some
knowledge that is what the data mining
is all about and it's also extracting
knowledge from the data which can make
some decision making effective it is
base to decision making systems
there's also extraction of
interestingness so when we are talking
about interestingness will be talking in
the further lectures how interestingness
is a parameter to be judged when we are
talking on data' mining and also it can
be used for searching algorithms and
you know for the query processing now
basically you know what is it that we
are talking about what is the difference
so data mining is not searching how is
it different from searching so we are
not writing queries it's not the
database the data mining is applied on
various forms of data so it's not always
that we are working with the same kinds
of data that's a concept of data
warehousing which we'll be covering in
some other lecture but in in order to
understand in simple words data mining
is not applied on single type of data
when it's query processing or maybe you
know writing the query in the databases
in the same type of data
additional task is also that we need
pre-processing we are talking on the you
know issues related to the data from
different sources so that is
pre-processing is performed and that is
the reason it gives you more effective
results now when we are talking about
the application how can we data mining
can be used the data mining can be used in
different parameters different fields in
a lot of ways so medical field as we are
mentioning here is one of the field
which is getting benefitted a lot by
data mining especially cancer detection
diabetes prediction and a lot of other
things so health data mining is one of
the causes of you know called cure for
lot of you know critical diseases and if
not the cure it is helping us reduce the
effects of the diseases ecommerce is the
only reason which you know data mining
came into existence and data mining is
one of the reason that e-commerce is
moving. The rise of Amazon and becoming
the you know the most come big company
is because of the data mining and
machine learning algorithms which they
have developed our webpage analysis the
results which we get prediction
algorithms in the stock market and so
much more so data mining is a diverse
field in fact I would like you to
comment in the comment section whether
you have heard of data mining in some
way or you experience or maybe you're a part
of the experience of you know data
mining is being done to you please share
your experiences now what kind of data
can be mined like I mentioned earlier
what's sort of data we can actually mine like we
can mine the relational databases we
have the data warehouses of different
types or a period of time a company or
industry or a Institute might have lot
of data so we can you know actually go
online and get those data perform the
pre-processing and find out if there are
some patterns or interestingness in
there there are sensor data is available
through IOT you know there is huge world
of IOT getting corrected with the help
of big data analytics so sports as the
field which is you know benefiting a lot
defense is something which is
benefiting a lot so this kind of IOT
sensor's data is used a lot time series
data if there is a data over a period of
time which we can use in a particular application
that can also be mined so there are lot
of applications we can also apply data
mining and visualizing and graphs are
also so this is what applications of
data mining are and in general it is a
very broad category we'll be seeing this
in the further lectures as well now
before we go further it's like what are
the major issues in data mining because
then we are talking about diversity of
the data when we are talking about huge
amount of data along with the benefits
there are a lot of disadvantages and
disadvantages is this as listed here is the
diversity itself can sometimes lead us
to you know miss conceptualize knowledge
the efficiency and scalability can be a
issue when we are talking about large
scale data also processing them requires
a hardware and structure which is not
always available user interaction is a
problem which we have sometimes the data
mining is you know we have to concern
about the society but at this kind of
information we can mine or not so data
mining in general is a very wide field I
guess at the end of the lecture you will
have a brief idea of what is data mining
thank you thank you so much for your
time and patience please subscribe to
Ed technology hope to see you again in
the next lecture thank you so much hasta
la vista
