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All if your goal is to become a data scientist, to orientate analyst, then you have to work smarter.

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You don't have to work harder.

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So what exactly is a best approach to achieve your dream job as a data scientist oriented analyst?

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You have to just showcase your practical skills.

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You have to just showcase your projects on your resume.

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That said, that's why we all have come up with five real world use cases of data analysis that will

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definitely help me out to your dream job interview.

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So if you guys are going to give your hundred percent to this damn good project, then your chances

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of being recruited in some top notch product based companies in the top MNC is going to definitely very

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high.

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So the very first use case that we all are going to cover is exactly of UBA.

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So we all out of it about over.

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So it is exactly are American tech companies that provide those services like rides for delivery, which

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is exactly known as overeats.

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And according to a survey, which is a decidedly has been done, it is estimated that about seven to

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eight million monthly active users we have an Uber.

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So just try to imagine how much you the amount of data we all customers are going to create with respect

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to Uber so we can analyze this huge chunk of data.

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And from this huge chunk of data, we can definitely come across with some meaningful insights so that

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we can represent what organizations that will maximize our business model.

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So now the caution that will come across what type of analysis we can perform on this over data, let's

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say we have to analyze what exactly is a rush at a particular location.

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And our SO using this amazing plot, which is exactly my point plott, you can definitely come some

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meaningful insight.

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Let's say we have to perform some kind of a spatial analysis where we have to analyze what exactly the

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Roshe at a particular location in New York City in a similar way.

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We can also analyze our troops in New York City and that is exactly a trend.

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Our race in New York City in a similar way, we can analyze much, much from this data.

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You can analyze what exactly the demand versus supply chart of overpack is as much and we can analyze

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whatever we want.

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So the second project is exactly my hotel booking.

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So they all are aware about these tech companies like oil.

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We will MakeMyTrip booking a lot of these companies that provide US facilities to book rooms of a hotel.

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And according to a survey, it is estimated that approx 50 million bookings happened in a month.

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Just try to imagine how much huge chunk of data users are creating whenever they are going to book a

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hotel room.

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Now, the question will arise what we can do with this data.

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So what type of analysis we can pull from on this huge chunk of data?

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Let's say we have to analyze what exactly the home country of a guest or we can see from which Zone

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Ghast are basically coming from performing a spatial analysis.

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We can definitely come with this conclusion.

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You're basically Gastar, especially from some European countries, in a similar way that I have to

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perform.

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What exactly the passive distribution of all the room times.

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It's a category where it's a category where it's a category.

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And this is exactly the distribution in a similar way.

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We can analyze this trend as well.

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What exactly the trend of the room price, what exactly the preference of a guest?

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As much as we want, we can analyze as much as we can.

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So what third project is most demanding project of I.T. industry, which is exactly covid-19 data analysis

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project.

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So we all are aware about this pandemic that is right now going in this world.

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So to lead this virus, almost kill two point three million people.

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So from this huge chunk of data, we can say this exactly that pretty map representation of our data

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to analyze which country has a maximum confirmed cases.

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And from this we can say, yeah, us it has maximum confirmed cases because it has a bigger block.

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In a similar way, we can analyze four confirmed cases, that's cases, recovered cases and active as

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well.

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In a similar way, we can analyze what exactly is our population to test on the issue here.

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We can simply analyze this is exactly my top countries in a similar way.

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We can analyze what exactly are the 20 countries that gets impact.

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Did badly.

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So these are my top 20 countries in a similar way.

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We can also analyze what exactly that has to confront ratio in worst affected countries.

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So this is exactly the trend.

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So whatever we want, we can analyze as much as we can.

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And our third project is basically related to our finance data analysis in which we are basically going

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to consider data of bank.

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So we all have a data of whether a bank is going to issue a loan to a particular customer or not, depending

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upon the tons of features.

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So from this huge chunk of data that we have to analyze this data so we can analyze what exactly the

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distribution of each and every feature that data has, that after it we can analyze what exactly the

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account holder distribution.

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From this picture, we can definitely come up with this inside.

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There are a majority of the users that doesn't have any security or deposit in a similar way.

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We can also analyze whether that education is going to impact on a willing loan or not.

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So considering this box spot, we can definitely come up with this amazing conclusion in a similar way.

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We can analyze what exactly that income distribution.

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Lots of analysis.

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We have the platform hypothesis testing as well on our data.

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So if you are planning for a financial analyst or a data analyst in finance companies, let's say bank

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and insurance companies, you can definitely showcase this project on your resume and you can definitely

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be highlighted for one last project is a most demanding project of I.T., as well as of some topknot,

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broad based companies, which is exactly my Amazon project in which we are going to consider data of

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Amazon customers.

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So we all are aware about Amazon is exactly an e-commerce company, which is a most popular shopping

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company in the US, as well as in many other countries of the world.

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And according to a survey, approx, 30 percent of the total shoppers around the world would choose

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its items from Amazon.

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So let's try to imagine how much huge audience this Amazon has, how much huge chunk of customers this

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Amazon has.

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So from this huge chunk of data, we can definitely perform some amazing sentiment analysis.

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And that's we can also analyze to what users Amazon is going to recommend more product.

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That's what we basically sees on our Android, on our windows in a similar way.

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We can also analyze what exactly is a distribution of feedback lant given by Amazon customer Rahnavard.

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He's going to buy some certain products in a similar way.

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We will also analyze behavior of our customers, what exactly he likes, what exactly he dislikes.

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So in a similar way, we can analyze this as much as we want.

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So you have to just give your hundred percent to all these products.

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Once you do all these, you are definitely much, much confident regarding all these projects.

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And you can definitely showcase this project on a resume.

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And you can definitely set your job as a data scientist, as a data analyst in some top notch project

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based companies and in top manses.

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So for what you guys are waiting for, just with me and have a fun.