All if your goal is to become a data scientist, to orientate analyst, then you have to work smarter.
You don't have to work harder.
So what exactly is a best approach to achieve your dream job as a data scientist oriented analyst?
You have to just showcase your practical skills.
You have to just showcase your projects on your resume.
That said, that's why we all have come up with five real world use cases of data analysis that will
definitely help me out to your dream job interview.
So if you guys are going to give your hundred percent to this damn good project, then your chances
of being recruited in some top notch product based companies in the top MNC is going to definitely very
high.
So the very first use case that we all are going to cover is exactly of UBA.
So we all out of it about over.
So it is exactly are American tech companies that provide those services like rides for delivery, which
is exactly known as overeats.
And according to a survey, which is a decidedly has been done, it is estimated that about seven to
eight million monthly active users we have an Uber.
So just try to imagine how much you the amount of data we all customers are going to create with respect
to Uber so we can analyze this huge chunk of data.
And from this huge chunk of data, we can definitely come across with some meaningful insights so that
we can represent what organizations that will maximize our business model.
So now the caution that will come across what type of analysis we can perform on this over data, let's
say we have to analyze what exactly is a rush at a particular location.
And our SO using this amazing plot, which is exactly my point plott, you can definitely come some
meaningful insight.
Let's say we have to perform some kind of a spatial analysis where we have to analyze what exactly the
Roshe at a particular location in New York City in a similar way.
We can also analyze our troops in New York City and that is exactly a trend.
Our race in New York City in a similar way, we can analyze much, much from this data.
You can analyze what exactly the demand versus supply chart of overpack is as much and we can analyze
whatever we want.
So the second project is exactly my hotel booking.
So they all are aware about these tech companies like oil.
We will MakeMyTrip booking a lot of these companies that provide US facilities to book rooms of a hotel.
And according to a survey, it is estimated that approx 50 million bookings happened in a month.
Just try to imagine how much huge chunk of data users are creating whenever they are going to book a
hotel room.
Now, the question will arise what we can do with this data.
So what type of analysis we can pull from on this huge chunk of data?
Let's say we have to analyze what exactly the home country of a guest or we can see from which Zone
Ghast are basically coming from performing a spatial analysis.
We can definitely come with this conclusion.
You're basically Gastar, especially from some European countries, in a similar way that I have to
perform.
What exactly the passive distribution of all the room times.
It's a category where it's a category where it's a category.
And this is exactly the distribution in a similar way.
We can analyze this trend as well.
What exactly the trend of the room price, what exactly the preference of a guest?
As much as we want, we can analyze as much as we can.
So what third project is most demanding project of I.T. industry, which is exactly covid-19 data analysis
project.
So we all are aware about this pandemic that is right now going in this world.
So to lead this virus, almost kill two point three million people.
So from this huge chunk of data, we can say this exactly that pretty map representation of our data
to analyze which country has a maximum confirmed cases.
And from this we can say, yeah, us it has maximum confirmed cases because it has a bigger block.
In a similar way, we can analyze four confirmed cases, that's cases, recovered cases and active as
well.
In a similar way, we can analyze what exactly is our population to test on the issue here.
We can simply analyze this is exactly my top countries in a similar way.
We can analyze what exactly are the 20 countries that gets impact.
Did badly.
So these are my top 20 countries in a similar way.
We can also analyze what exactly that has to confront ratio in worst affected countries.
So this is exactly the trend.
So whatever we want, we can analyze as much as we can.
And our third project is basically related to our finance data analysis in which we are basically going
to consider data of bank.
So we all have a data of whether a bank is going to issue a loan to a particular customer or not, depending
upon the tons of features.
So from this huge chunk of data that we have to analyze this data so we can analyze what exactly the
distribution of each and every feature that data has, that after it we can analyze what exactly the
account holder distribution.
From this picture, we can definitely come up with this inside.
There are a majority of the users that doesn't have any security or deposit in a similar way.
We can also analyze whether that education is going to impact on a willing loan or not.
So considering this box spot, we can definitely come up with this amazing conclusion in a similar way.
We can analyze what exactly that income distribution.
Lots of analysis.
We have the platform hypothesis testing as well on our data.
So if you are planning for a financial analyst or a data analyst in finance companies, let's say bank
and insurance companies, you can definitely showcase this project on your resume and you can definitely
be highlighted for one last project is a most demanding project of I.T., as well as of some topknot,
broad based companies, which is exactly my Amazon project in which we are going to consider data of
Amazon customers.
So we all are aware about Amazon is exactly an e-commerce company, which is a most popular shopping
company in the US, as well as in many other countries of the world.
And according to a survey, approx, 30 percent of the total shoppers around the world would choose
its items from Amazon.
So let's try to imagine how much huge audience this Amazon has, how much huge chunk of customers this
Amazon has.
So from this huge chunk of data, we can definitely perform some amazing sentiment analysis.
And that's we can also analyze to what users Amazon is going to recommend more product.
That's what we basically sees on our Android, on our windows in a similar way.
We can also analyze what exactly is a distribution of feedback lant given by Amazon customer Rahnavard.
He's going to buy some certain products in a similar way.
We will also analyze behavior of our customers, what exactly he likes, what exactly he dislikes.
So in a similar way, we can analyze this as much as we want.
So you have to just give your hundred percent to all these products.
Once you do all these, you are definitely much, much confident regarding all these projects.
And you can definitely showcase this project on a resume.
And you can definitely set your job as a data scientist, as a data analyst in some top notch project
based companies and in top manses.
So for what you guys are waiting for, just with me and have a fun.