Data analytics Roadmap 2025 | data analysis job market | how to prepare | tips

you have to do data cleaning, data manipulation, you have to do data analysis, and then you have to create. So what is data analyst? Data analyst in 2025. So hello everyone, welcome back to my YouTube channel, your go-to channel for your career tips. So now we are going to talk about very interesting, trending, and topmost question which is asked by every candidate over here, that how to get a job as a data analyst. When you wanted to get a job as a data analyst, first you should understand what exactly data analyst is. Data analyst is a job role where you have to work on data, and that data you have to do data cleaning, data manipulation, data analysis, and you have to move to the data visualization. You have to create dashboards, and then you have to share the insights to the team or the client about the data. This is what data analyst is. Now, what other candidates are doing wrong and what you need to stop and you have to avoid? First thing is they all are searching about data analyst, right? But you don't have to do that. You have to be specific for the job role that you are applying. Yes, that's correct, job role, but you have to also go with the domain. Suppose I am a candidate who is interested in domain which is finance. I'm more into maths, I'm more into calculating the stocks and all, then I can simply apply for financial data analyst. If someone is interested in healthcare, then that person has to apply for healthcare data analyst. If everyone will keep on applying to the data analyst role, you won't get any job in your hand. You have to apply for the role that is of your domain, of your interest, then only you will get the job. So here is a complete list of the data analyst job roles that you have to target for. Now let's move on to how you can get a job in 120 days. Yes, I am taking a target of 120 days that I'm expecting that within 120 days you can get a job after completing your internship event. So let's see what you exactly have to do. Before we dive into the 120 days roadmap, we now discuss about the skills that is required, because knowing what exactly you have to target is very important. So if I talk about technical skills, then in technical skills, the topmost skills is you have to learn about Microsoft Excel. Now Microsoft Excel, what exactly you have to do is you have to learn about how to do data cleaning, data manipulation, and how to create dashboard. That's it. Second skill is the skill of database. You have to learn about SQL, MySQL, PostgreSQL, database, uh, servers for getting a data analyst role. Because company stores data in the databases, that is why you have to learn it. Third is the Python programming language, or I can say programming language because you have two options, Python and R. I would recommend go with Python because Python is good language for career upgrading. Now the next skills that you have to learn is data visualization. You have to learn about some tools that can help you in data visualization like Power BI, Tableau, Google Analytics. There are many more tools available in market, but there are top two is top Power BI and Tableau. And for my recommendation, go with Power BI. Then you have to learn about the soft skills. Now soft skills is not something which you have to learn, you have to practice basically. So first topmost soft skill that is required in every job role is communication. If you wanted to get in the job of the technical job, like if you are switching from non-tech to tech, communication is very important. Even in non-tech also communication is important, but over here in the data analyst role, communication plays a major role because whenever you are done with the data visualization, you are done with the dashboard creation, then you have to convey your insights to the team. While conveying, you have to make sure that makes sense to the non-tech team. So that can be only done with the storytelling. So first is communication, second is storytelling, third is you should have a confidence because you are going to portray everything. You are— will be the front face for the company or the clients. Now let's talk about 120 days roadmap that I am talking about. Now let's talk about Phase 1. In Phase 1, you have to get the foundational knowledge of all the skills. So our target is to achieve the data analysis basis. Then you have to also target about learning the foundational tool. Third thing is your analytical thinking, because that is must in data analyst role, because we are going to solve the business problems. So our target is 3 within the 30 days. So you have to just focus on these 3 things. You don't have to try to learn everything. If you will try, you will end up with nothing. So you have to try to cover these topics that what is data analysis, what type of data do we have, structured data, unstructured data, how to deal with unstructured data, what are the steps that, that is required that others are following and all. And then you have to also choose your career path that in what domain you are interested in. Are you interested in HR, healthcare, marketing, supply chain? In which one? According to your previous past experience also, you can choose the domain for yourself. Next is you have to explore Excel, Microsoft Excel. You have to explore, you have to do data cleaning, data manipulation, and then try to just create dashboards on it. Small charts, not a complete dashboard. Then you have to learn about introduction to the databases, like what are the type of databases, which one you have to learn. I would recommend go with the Microsoft Excel in this stage. And then on the next stage, you can go with the PostgreSQL as well. Both are trending these days and many companies are using this too. For this, you have to learn about basic statistics, that mean, median, mode, and just a bit of it. And because everything is going to be done by the library's functions only. Now let's talk about the second phase. This is the intermediate skill phase, which I call, and this is again the 30-period goal, that there are two goals for you. First is you have to achieve hands-on experience. You have to try to practice a lot rather than learning. Or going theoretical or, you know, watching tutorials only. You don't have to consume tutorials, you have to create something by yourself. No matter how many errors, no matter how good or bad project are going to be, you have to do the hands-on practice. You have to learn data visualization and storytelling. After creating a small dashboard, try to record yourself, you know, the same way you are talking to someone else. You have to just try to share some insights to the second person so that it helps you in storytelling and improving your communication skills as well. In this phase, you have to learn about Python programming language for data analysis. Focus on some libraries like Pandas, NumPy, SciPy libraries. You don't have to learn about the basics a lot. You just get the foundational knowledge of Python programming language, that how to exactly write code, how to write functions, how to apply functions. That's it. You need not to go in depth of the foundation or the basics of Python because that is not required for the data analyst role. The main Requirement for the data analyst role is the Pandas library, NumPy library, or any other library which is going to make the analysis happen. Anywhere, what you have to do is you have to try to create a documentation of what you are doing. If you are going to skip this step, then you will end up with nothing by the end of your learning. You should get your project so that you can add it in your portfolio. Second is you have to explore the data visualization tool in the second stage because this is your second month and you have to go with the Power BI, Tableau, and other tools whichever you have selected. Recommendation is go with the Power BI. Then you have to try to go with the domain knowledge as well. You have to do the financial data analysis. You have to do— go— if you are going with the HR analysis, you can go with the employee attrition or recruitment analysis kind of project, so that whenever you're going to add it up in the portfolio, that makes sense to the recruiter as well. Now let's talk about the third phase. This is the analytical phase. In this phase, you have to focus on two things. Your key roles are you have to master these tools. Those tools which are good for your real-world application. Not everything is good for your real-world application. Second is you have to learn about the machine learning basics. Yes, machine learning basic is required for data analyst role. If you have the machine learning knowledge, then you can help in the data science, a bit of data science role as well. That is clear. Now let's talk about topics that you have to cover. You have to cover the advanced SQL, advanced Excel. You have to cover the predictive analysis. You have to learn about specialized analysis techniques that is relevant to your projects as well. Now let's talk about the Phase 4. This is the last phase. Now in this last phase, you have to talk about real-world application of whatever you have learned, how you can imply— apply all these things in your projects. Now there are two goals. First is you have to build a strong portfolio for yourself. Second is you have to gain interview-ready confidence. Now after completing your two months, which is the Phase 1 and Phase 2, you can start applying for the internships. Once you get the internship, there are several platforms that you can use for internship. Now once you are in the fourth stage, you have to build a portfolio for yourself in which you can include the projects that you have created in interviews or you have created in while you were doing volunteering and all. Anything it could be, have to add those projects in your portfolio so that you can display them in front of the interview. Now in the fourth stage, you have to learn about the advanced techniques using Python and SQL like data cleaning, data transformation. You have to learn about big data basics as well. You have to build your portfolio. There is a— there's a separate video on my channel on which I have explained how you exactly have to do the portfolio building using Python. If you wanted to go with Python, go— you can check out that video. In the description, I have added a link of the video that clearly explains how you exactly have to build portfolio without any coding as well. There's a key thing to note that whenever you are applying, whenever you are going to, you know, start learning this, there is a daily commitment required. You have to try to give at least 3 to 4 hours for this job role because this requires technical skills. And if you are switching from non-tech to tech, then your focus is must. Here is a job portal which you can use for getting the jobs. This is a list of job portals which you can apply for. You can just go sign up and turn on their notification, and on your mail regularly you will get the notifications from them that this is the hiring, and you can select, give your preference as well. Second thing that you need is that which company you have to target for. So if you are looking for tech companies, then go with the Google, Microsoft. These are the MNC companies, but there's a huge list of tech companies as well. So on my screen you can see these are the companies that you have to target for, and once you are ready with the confidence and with your portfolio, you can go with this. Now for job application, what all things you required? First thing is your portfolio. You should have a good portfolio. It can be coded or non-coded, that totally doesn't matter. You just have to showcase it in the good manner so that it should be like with the clickable links, There should be a dashboard like which is, which is visible to the recruiter as well. Second thing is you need a resume and a letter, a good cover letter focusing and targeting the company itself for it which you are applying for. So these two things are required for your job application. Apart from job application, there is a recommendation for you that you have to try to build a complete, a good network on LinkedIn, on any other job profiles. These days companies are hiring on the basis of Stack Overflow, profile or Reddit profile, or if you have created any LeetCode streaks like on the basis of pandas library and all, or SQL and all, that is a good way to get hired as well. So don't forget to put yourself on these platforms as well. So I hope this video was informative for you. Do let me know in the comments and what other topics you want me to cover on this channel. So we'll meet in the next video. Bye-bye!