How to Become a Data Analyst in 2024? (complete roadmap)

data analytics was a hot career last year the year before and it's not going anywhere in 2024 so if you have been wanting to become a data analyst then you have clicked on the Right video because in this video I'm going to be sharing data analyst road map that you can use to become a data analyst in 2024 there are three ways to become a data analyst you can earn a degree you can take boot camps which is a condensed version of degree program and third you can do self- teing in this video I'm going to be focusing on self- teing and how you can learn different subjects in data analytics to become a data analyst in my opinion learning data analytics is not that difficult for somebody who is just starting out they probably have no idea where to get started what to learn so this video is specifically dedicated to you so before we talk about the road map let's actually talk about what does a data analyst do so businesses are collecting a ton of data and they want to make data driven decision and that's exactly when a data analyst comes in they help the company make datadriven decision using that data so data analyst in this case would be looking at historical data understanding performance where things are going well where things could be improved and helping business guide into making a decision that would help them grow in the future and this is why data analyst's role is specifically important to any company because a data analyst is basically telling you what's happening with your business so you can make data driven decisions data analyst falls into the data science umbrella there are several roles in the data science umbrella including data scientists machine learning data engineer AI Specialists but in this video we'll be focusing on data analyst topic before we jump into the road map I want you to do one exercise I want you to research the role I want you to figure out what your target data analyst role looks like what your target company looks like let's say your target company is Amazon in this case you will go to Amazon career website look up data analyst role read the job description and try to understand what are are the skill sets that they are asking for what are the tools that they're asking for what is the language that they're asking for you're going to take a note and write it down and we're going to come back to this the next thing you're going to do is you're going to go to LinkedIn and find somebody who is already working as a data analyst at Amazon and you're going to see what their background is did they take any specific courses did they take any specific certificates basically try to understand what their day-to-day work is like and what exactly is their background and you're going to make a note of that information as well now you have basically created a data set based on your research of the role where you will use that data and work backward from it for example let's say your target company prefers that you know how to work with Google Sheets and Tableau or in Amazon's case Amazon loves to use their own specific native AWS products such as quick site is one of the tools that they would be using so you might see that on the job description as well as somebody who is working there so by doing this exercise you actually are basically creating a road map for you which gives you an idea of like okay what's your end state looks like where do you want to go and this is actually really really helpful I actually do this for all of my work not just for learning something new but also like when I'm doing like my project scoping I try to figure out like what exactly do I want to what does my ideal outcome looks like so it's very similar to that you're doing project management of your data analyst learning road map so let's say you have understood the role you know what you want to do what your ideal role looks like now we're going to jump into that road map there are a few things that I'm going to be mentioning I'm going to be talking about how much statistics and math you need to know what coding languages you need to know what tools you need to know I'm also going to be covering some soft skills as well as project and Hands-On work and finally ending with interview prep so we're going to be covering a lot in this video so start taking notes so the first thing I want to talk about statistics math and data analysis fundamentals for statistics I would suggest that you start with understanding descriptive and inferential statistics descriptive statistics is like a summary of your data or a snapshot of what your data looks like it basically helps you understand main characteristics of your data inferential statistics is basically taking it one step further it's taking the snapshot of the data and making educated decision think of like experimentation prediction and things like that that's where you will be using inferential statistics to understand your data in a more educated way and make predictions from it this is a visualization that basically explains what is the difference between statistics and an inferential statistic you can learn these topics from anywhere you can pick any book that talks about these two topics just make sure that it's focused on data analysis so that learning can be catered to like your needs for math I would say you need basic understanding of arithmetic math and algebra although you would likely not be using as much math it's likely when you have to do some statistics or some machine learning work the chances of you doing that as a data analyst is low but it's always good to have some knowledge of math the third thing that I would like you to cover here is some data analysis fundamentals what does it mean when we say data cleaning data collection like understanding understanding what each of those terms mean so you are able to talk in a data analyst language there are several resources for learning all the statistics math and data analysis there are YouTube channels I love KH Academy for learning stats and math definitely a great resource for data analysis fundamentals you can pick up any book so one of the free resource that I found on learning data analysis fundamentals is this free ebook called introduction to data analytics this ebook is created by HubSpot who is also sponsoring this portion of the video the EB book covers data analysis fundamentals and starts from like very basic such as data cleaning data collection and then jumps into more advanced topics such as bias versus variance which is one of the topics that you will need to know for inferential statistics it also talks about what are some use cases for using generative AI when it comes to doing data analysis which I think is like really cool there's several other examples that are included for the types of data analysis and data analysis methods that you can use as a data analyst all in all this is a super handy ebook to have by your side when learning data analytics and the best part is that it is free it's linked in the description below so feel free to download it now let's say if you have learned the statistics math and data analysis fundamentals then we're going to jump into tools for tools learn Excel Excel is the bread and butter the chances are you're going to be spending a lot of time in Excel or Google sheet depending on what your company prefers so become very comfortable with Excel some of the things that you should do in Excel is data cleaning sorting creating pivot tables writing formulas to do descriptive statistics learn how to do data visualization in Excel and also learn how to make it pretty because everybody loves pretty reports and pretty Excel files Excel and Google Sheets can be very similar so I would suggest to focus on one and then you can easily transition to other now if you have done your research and you understand that your target company and Target role uses a tool like Tableau or something like quicksite or looker Studio then you will kind of like Target which tool to learn based off of that let's say the role that you looked at what preferred learning Tableau so let's say the research that you did based on that research you learn that you need to learn Tableau as a data analyst so that's where you would kind of like start learning Tableau and figure out what kind of things that you need to do in Tableau whether that is like creating reports doing visualizations and so on by learning this tool you should be able to make reports and visualizations in these tool because the chances are when you're working as a data analyst the business stakeholders will come to you and will ask you to build reports in a tableau or a quicksite or a looker Studio type of tool so learning this tool is definitely going to be helpful so highly recommend that you pick one and build on it and then eventually you can transition between the tools but just picking one and sticking to it just simplifies your learning process these two things you should definitely be very very comfortable with now let's say you have learned these tools the next thing that you should be doing is learn the coding languages obviously the first and primary coding language that I'm going to mention is SQL and I don't even have to say it you need to know SQL because the chances are that 90% of your time as a data analyst you will will be using SQL there might be a 5 to 10% chance where you will be using python but if you are starting out in coding like definitely understand how to write your select statements how to get data from a database using SQL how to do filtering how to join multiple data sets how to do aggregate analysis how to use Advanced analytics function in SQL basically understanding logic is very important as well in addition to like understanding SQL syntax so definitely do a lot of practice on learning SQL you can also Learn Python but make sure when you're learning python focus on python for specifically for data analysis because you can easily get lost when it comes to learning python I have done a few videos for learning python data analysis you can watch one of those to get some ideas obviously you can use generative AI to kind of like help you create a road map here and figure out what topics you need to learn another cool thing that I would like to share here like if you're going from SQL to python it's also helpful that you use tools such as chat GPT to help you learn I have personally asked it to convert coding language for example you can give it SQL group ey and say can you convert this to a python coding snippet and then you can kind of like learn through that process that how you would do a group by in python or how you would join two data sets in Python so just a tip here if you are going from SQL to python python again is super intuitive and it's easy to learn so definitely add it to your toolkit for doing data analysis by now you have basic understanding of stats maths data analysis fundamentals you know which tools to use you know how to use them you know the coding languages as SQL and python now we need to work on your soft skills by now whatever I have talked about it's called hard skills because these are the skills that you need to note in order to do your job now in order to do your job effectively you actually need to have soft skills and by soft skills I primarily mean communication and storytelling when you're doing your analysis when you're doing your work at the end of that analysis or even at the start of your project you actually need to understand the problem and the only way that you can get to the core of the problem let's say if a product manager comes to you and I ask you to do some data analysis you need to ask them questions back and you need to understand what exactly they're trying to get to because sometimes stakeholders ask you question when they don't exactly know what they want so by you asking them questions and trying to understand the problem you are able to get to a better solution similarly at the end of your project you actually you have to present your work whether that you do it verbally or you do it in a written format or you do it in a presentation format so get better at communication get better at writing get better at storytelling because that would make you effective data analyst there are several ways to practice that you can practice it at home with friends in front of a mirror with a camera write blogs get more Hands-On writing experience all these things like make you a better Communicator I don't know if that's a term but basically you need to have really good soft skills in order to succeed in a data analyst career after doing all that you basically have the toolkit for data analyst now you need to do Hands-On project and build your portfolio so you can show it on your resume there are several ways to approach this one is that you can Define your your own problems for example you can look at your credit card purchases over the last 6 months and you can try to analyze it or for me I can do like how much I have walked between the different months of the year and I can do analysis on that I can do cool visualization so that's one way to kind of like figure out what your project should be the other is that you can also like go to these websites a website called analytics Vidya which has like specific problems and data set given to you and you can like build the data analysis project around it now the reason I am saying that there are so many ways that you can do projects because I want you to do it the only way you can learn is if you do it and if you don't do it there are two downsides to it one you don't learn it might seem like that you have learned it but eventually you'll forget it and second it helps you build your portfolio that's how companies are going to know that you can do the data analyst work and that's how they're going to be able to hire you so you need to do the Hands-On work you need to figure out your projects and you need to kind of like start building your different project portfolio you can also find free data set on several sources such as like kaggle has free data sets it also sometimes has the problems along with the data set that you can use the data set download it and solve for that problem there's also Google data set search that you can use to download free data based on your interest on anything well not anything but like most of the topics are covered and you can kind of like build your projects around it one of the other platforms that I mentioned is analytics viia has a lot of problem as well as data set available if you thought you were done you're not I have one more step because I really want you to be ready for real world and the only way you can be ready for a real world is if you are able to land a job and the only way you are able to land a job is if you do the interview prep you have done all the hard work you have learned the statistics math data analysis fundamentals you have learned the tools you have learned the coding you have figured out your communication you have done Hands-On project you're applying for jobs and you're getting a call now you need to pass that interview in order to get that job so this is where you need to kind of sit down do your research figure out what kind of questions your dream job your target company is asking for that Target role that you have and start practicing and do a lot of practice one of my favorite ways to do is is I anticipate the question I write it out on a document and then I practice it this is more for like behavioral questions and then I practice with the friend I do mock interviews with the friend because the problem is that even though it might seem like that you know it when you are in a pressure setting talking to somebody else sometimes you forget and sometimes you're not able to identify what things that you could be saying better or shouldn't have said your friend or or the person that you're mock interviewing with is going to help you figure those out so do a lot of mock interviews do a lot of interview prep do a lot of Hands-On SQL problems python problems is that what they're asking one of my favorite platforms obviously you can use lead code one of my favorite platforms that is more focused on data analysis and data scientist work is St of scratch I'm going to link them below as well so make sure that you're prepared for the real world because the goal in doing all of this work is to land a job and enter your career as a data analyst and only by having good interview prep you will be able to work as a data analyst and be able to get into your target role that we discussed at the start of the video all right that's all I wanted to say thank you so much for watching if you found value in this video give this video a thumbs up because it will help with the algorithm and let me know in comments if you have any thoughts or questions and I will see you in the next video have a good one bye

Channel: Sundas Khalid

Views: 204,200

Keywords: data science, data scientist, self-taugh data scientist, tech jobs, big tech, Machine Learning, Python, data science projects, data science tutorials, data science jobs, data science day in the life, AI, big data, data analyst, data analytics, business analyst, sundas khalid, women of color in tech, people of color in tech, inspiring stories, data science at google, data analyst roadmap 2024, data scientist roadmap 2024, data analytics career, chatgpt how to use

Id: iYiD2Ray9Bk

Length: 14min 21sec (861 seconds)

Published: Mon Jan 01 2024