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5 Reasons why you SHOULD NOT become a Data Analyst (in 2024)

Mar 31, 2024
There are 101 different videos telling you why you

should

become

a

data

analyst

in

2024

, but the only thing I don't see on the internet is why you

should

n't

become

a

data

analyst

and whether you hate certain things you have to do during the day. Today, as a data analyst, these are all questions that we will go over in this video. Today I'll go over the top five

reasons

why you shouldn't become a data analyst in

2024

if you're new. for this channel my name is Rohan and in this channel we cover everything related to data analysis. In fact, I have a Discord server down with almost 2000 people who are dedicated to analysis here, they are actually doing projects day to day or networking with each other, they are people who are already working in the field and people are mentoring others people trying to get into the field, so if this sounds like a good option to you, I recommend clicking the link below and joining the server.
5 reasons why you should not become a data analyst in 2024
I would love to see you there, so before we begin I want to tell my story of how I got into this field. I started my career in finance. I actually worked at an asset management shop and quickly realized this wasn't for me after this. I actually took a data science and analytics class and this professor really stood out to me. I was always terrified of anything related to coding or programming and I'm sure many of you are in the same boat today and may be intimidated by the fact. You have to code in Python or SQL, but the only mindset that changed when I talked to my professors is that you have to think of coding as a tool, just a language.
5 reasons why you should not become a data analyst in 2024

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5 reasons why you should not become a data analyst in 2024...

People who are good data analysts are not the best coders. They are the people who can apply the tool and code to what they want to do and this brings me to my first point. If you don't like math or statistics, you might not like being a data analyst. I'm not telling you. you need to have a PhD either way or you don't need to have a math major, maybe it will help you, but you don't need to have them. Mathematics and statistics as a data analyst are very easy to obtain, but you must enjoy them.
5 reasons why you should not become a data analyst in 2024
You have to understand that data analysis is analysis, you are doing analysis and we are doing analysis using statistics to help you with those experiments, so almost everything you are going to do as a data analyst comes down to statistics, mathematics and experimentation. So if you don't understand what bias is when an AB test is what sampling is random sampling, you'll quickly realize that being a good data analyst, a high-quality data analyst, requires a certain degree of comfort with mathematics. and statistics, and Many of you may be surprised by this information, almost all how2 videos on how to become a dat in 2024, it doesn't even mention mathematics, it doesn't even mention statistics, a lot of information available is correct, you need to know SQL. you need to know Python at least a little bit of Python or you need to know some kind of business intelligence tool, be it Powerbi Tableau, but the only thing you are missing is statistics and mathematics; actually, there's a great course to learn fundamentals of probability and statistics for data science and data analysis uh, it's called practical statistics for data science.
5 reasons why you should not become a data analyst in 2024
I'm not going to leave an affiliate link below, you can search for it on Amazon, but that textbook is the Holy Grail. Many people seem to get confused: you don't need to be an expert to get into this field, you just need to know enough to get your first job and pass that interview. This is something that lasts a lifetime and you will do it constantly. Constantly learn and improve your skills. The next reason why you might not want to become a data analyst is that you don't like to communicate, you don't like to present. A lot of students come to me and say, Hey, I want to become a data analyst.
Analyst because I don't like talking to people. I like being upside down. I want to work for weeks and not interact with many people, but that is far from the truth. In almost every role I've had, I've had to depend on others. the stakeholders, whether it's data, the engineers to get my data, the software, the engineers to record that data, the product managers who did the analysis for you, are constantly talking to people and don't make me start when they are waiting for someone to give them. give you some data, give you a report or respond to an email, these are all communication skills and interpersonal skills that you need to master, so thinking that you are going to work just to be completely self-sufficient, it doesn't work that way.
In a company you have to be willing to communicate and work with people. Secondly, many people get annoyed by the fact that you have to present your work. They think that it is enough to carry out an analysis and do a good job. I'm sorry to tell you that's enough. you, that's half the battle, the other half of the battle, selling your work and presenting it properly if you do a great analysis that's great for you, but will people actually act on the analysis that you do? Will they really act on the insights you provide and what this boils down to is selling your work through a presentation.
You must first understand your audience. Figure out the best way to introduce them. Could it be an email? Can it be a written report? Will it be a live Q&A session? session or it can be a video like I'm doing now and it comes down to who your audience is and what you want your audience to do. Let's go through a quick example, let's say you're talking to a sales team and they If you don't really understand the methodologies, the statistics, or what tools and languages ​​were used to perform this analysis, you might want to do a live Q&A session. to answer the questions on the spot because if you just gave them a report, it's up to them to interpret what you're saying and they might not understand exactly what you're saying and what they're supposed to do, but on the other hand, if you're talking to a data scientist or a data analyst who are very technical, maybe a report is enough, they will understand exactly what AP value is exactly what a split test is.
There is no need to fill in any gaps that they may not know yet, so understanding who your audience presents and communicates to is a very integral part of being a data analyst in 2024, the next reason is that if you are not resilient, if you do not have a strong mindset, this may not be for you, you're going to fail a lot and trust me, no matter how many or how many new jobs I get. new industries I join the first 6 months to a year it crashes constantly you don't understand the systems they use you don't understand who to communicate with you don't understand the domain these are all the things you need to consider I'm not going to get it right the first time, this could also be just with an analysis, maybe you're just not debugging the code correctly or maybe you're pulling data from somewhere and it's just not accurate and you don't know how to get it. accurate data from that source, so you're constantly checking the data, but it all comes down to resilience.
You have to have a strong mentality because it's not going to be perfect. The work is not going to be perfect. You know how you have it. that clean data structure in kagle or google data sets that you are playing with for your projects in the real world, real data sets are not like that, they are messy, extremely messy, so a lot of your work consists in being resilient and finding out where the errors are if this data is accurate and people will be fine if I use this data because if you go to someone with bad data and they criticize you, you will lose your credibility as an analyst and lastly, I'm sure that Not all, what is now becoming data analytics is a very steep learning curve and those who are not resilient will not last on this learning journey.
It's constant. Once you get your first job, you can't always stop learning. You have to keep learning, you always have to resist. This brings me to my next point. One of the most common misconceptions about data analysis is that it is a very sexy and glamorous job and I don't blame you. I think there were some articles written that say Data Science is the sexiest job of the 21st century and I'm not kidding. I have colleagues who literally became data analysts because of this, just for the prestige, the name or the salary, whatever the reason, but there is one thing that is not talked about. in these articles or people in the industry trying to glamorize it, 50% of your job is boring, repetitive, monotonous and no one wants to do it.
The good thing is for you with AI. I get this question frequently. Will AI replace the data analyst? Will AI help you as a data analyst? You'll get rid of that boring job you didn't want to do. A lot of your work will be data preparation, data cleaning, and you know what that's like. scan your data set delete null values ​​delete duplicates change the format this is not sexy this is not fun no one wants to do this job and sometimes you also work with security concerns privacy concerns because not using all the data sometimes is not No It's ethical because of privacy restrictions, but what I will tell you first hand is that AI will replace a lot of these boring things that you don't even want to do and you will be able to focus more on the fun parts, like just analyzing, interpreting data and giving insights. actionable, the more important, the more fun and sexy the data analysis part is, so if you don't like boring work, this may not be for you, but who knows for how long, what if A.I.
Come only to representative places and outsource all the boring work? I just don't want you to have the expectation that everything will be fun in games and that they will be things that you will enjoy doing, but I mean, that's the same with any job, right? And the last reason why it may be It wouldn't be a good idea to convert one day in 2024 if you don't like learning. Look, I've mentioned it several times in this video. This is a learning journey that comes to this landing. Your first job is the first step. Tools are constantly changing. which were popular 2 or 3 years ago, they may not even be popular today, the dashboard bi tool that everyone used before was powerbi Tableau, now all I see is people using google search and such Maybe the next 10 years will be a different tool.
What I mean is that you always have to like learning and you always have to be improving your skills at work. What are the new tools? What are the new technologies that are emerging? One of the biggest changes taking place in the technology industry or simply in the corporate world in general is the shift to the cloud. The difference between the cloud and traditional on-premises servers is that big companies like Amazon, Google, Microsoft have servers that they rent from other companies, so you don't have to pay for your own company's on-premises servers. I know that may sound like a lot, but the cloud is taking over and you have to learn how to be a data analyst in the cloud, how to use a data warehouse, what is the best data warehouse tool, Amazon Red Shift Snowflake and understanding these different concepts, like Data Lakes data warehouses, but When you first get your first job, don't worry about all these things, but all I'm saying is that you should be prepared to learn and improve your skills. constantly, not just to get your first job, one of the most common mistakes.
What I see people do is they think they need to be a mastered sequel to a master Tableau, but that's not true. To get your first job, you only need to know enough to pass that interview and the way people become great analysts is through work experience, you need time. really practicing what you're doing and a lot of times those projects or those fabricated school assignments don't reflect what you're going to do at work, so to become really good at your job as an analyst, it's all about practice and working there and constantly learning, if you do the same thing for 10 years you're not really going to get better, you have to learn, apply what you're learning and improve your work, and it's just a constant cycle for the rest of your career.
I want you to remember that your career is like a journey: many people become data analysts first, this is the end result, they may become data scientists later, they may become product managers later, just because now you are trying to become a data analyst. That doesn't mean you're going to be a data analyst forever, you should think of becoming a data analyst as a stop on a journey rather than a destination. Now I know most of you will consider these

reasons

. I gave these five reasons and I think yes, I knew it, it all sounds good to me.
I'm totally fine, but there will be a small percentageof you who will look at these reasons and freak out and say, "Hey, should I keep chasing?" this and those of you I want to ask this question which jobs have no defects which jobs have no disadvantages every job will have a negative aspect no job is perfect many of these issues that I am mentioning Here there are problems in every job. Many jobs will require you to communicate with other people. Many jobs you will have to work with other people. Many jobs you will have to constantly learn.
No job is just the same thing every day, so many of these disadvantages are found in many different industries. My advice to you is to choose something that interests you, choose something that pays well and choose something that gives you satisfaction because nothing is perfect in this world. I'm wrong. I know I'm making this video because I want to give you insight into some of the not-so-glamorous reasons to become a DAT analyst, but I want to make this very clear. I love being a data analyst and I think it is one of the most rewarding careers that exist right now.
Think about it. You can be creative. You can create dashboards with your own creativity. You can communicate. If you are an extrovert, you don't. You just have to make sales. You can talk to others. your clients and lastly, if you like numbers, if you're a math expert, you can do analysis with Statistics, so it's a good combination of a lot of different things. and lastly, I'm sure many of you know that this pays very well because of the skills you really need to know to become a dating analyst, so if you found this video helpful, please leave a like and subscribe , it really helps the algorithm. and it really helps me and see you next time

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