Roadmap for Transitioning to Data Analytics in 2023

if you're working or studying in another field how can you transition to data analytics many of you have asked me this question some of you may have a University degree in an unrelated field or working experience in something completely different essentially there are two ways to get into data analytics first is to completely self-taught and then cleverly combine analytical skills with your current domain knowledge either from your earlier study or jobs to gain extra comparative advantage and second is to take a data analytics degree or boot camp in this video we mostly focus on the self-taught route with the target of becoming a data analyst which is a good starting point to a lot of data science roles this is also how I start six years ago back then I was excited about Healthcare analytics so this is the area I start with in this video we talk about what you should learn and prepare in terms of the skills portfolio projects and how to approach recruiters things are changing so rapidly with many concerns around the develop government of AI and how it may affect you when pursuing data analytics career I also share some insights on this later in this video there's a lot to cover however if you want a more guided and result guaranteed route I'll also briefly share with you the option to take a boot camp for example the data analytics program by career Foundry who has kindly sponsored this video let's get started there's a lot of different job roles that involve working with data and turning into insights long ago people who did this kind of job would be called statistics nowadays I find that sometimes people are too hung up on titles and it can get confusing really fast if we look at job postings we see business analysts research analyst analytics consultant Junior data scientists and so on not to mention data analytics plus X kind of jobs that are roles that are specific to a domain such as HR data analysts sales analyst marketing analysts and so on to avoid the confusion I find it more useful to understand the nature show up the job and what skills you actually use so in this video I'll simplify all these titles as data analyst a data analyst is someone who analyzes data and data analysis is a process of inspecting cleansing transforming and modeling data with the goal of discovering useful information and informing conclusions and decision making so working as a data analyst can give you a very great foundation for you to progress into Data scientists or data engineer or other kind of data science job roles the median salary of a data analyst is 95 000 in the US the demand keeps Rising for people who have the domain knowledge and at the same time know how to analyze data as a data analyst you have the opportunity to work in many different domains like healthcare Finance banking Logistics human resources and so on you can work in startups agencies corporates or consultancy firms like I do you can choose to work full-time or freelance basis or even remotely so you have a lot of flexibility in your career which is really cool when it comes to the most important skills for a data analyst let me show you this skill model to help you visualize it on the most fundamental level you need some math and statistics just basic high school or undergraduate math and statistics will be sufficient unless you want to do more advanced stuff or machine learning in your job most of the times as a data analyst you do some descriptive statistics on the data like calculating the average mean Max median standard deviation Etc depending on the projects you might also want to do some outlier detection hypothesis testing linear regression or clustering or even machine learning so it really depends on your job and your projects secondly a data analyst would need some tools they are hard skills that involve using specific Technologies or software as a data analyst you want to get three things done almost on a day-to-day basis extracting data analyzing data and visualizing data to communicate insights and tell a story there are many tools available that can help you with each of these tasks or all of them if you're not sure which tools are most relevant look Burrows built a great website for exactly this purpose he collected and analyzed real-time job postings around the world you can look for the technical skills are most often required for data job according to the data the most in-demand skills for data analysts are SQL Excel Tableau Python and R you can choose to learn power bi as well but I think if you know Tableau then power bi should also be quite easy to learn in recent years and in the future many data analysts will work with big data so it may be useful for you to learn the Big Data versions of these tools as well such as box SQL for querying big data and also buy spark for working with big data in the pythonist stuff on the next level we have soft skills it's super important for data analysts to be able to communicate insights because you're going to be working with business stakeholders with product managers and other key stakeholders you're going to need to ask questions and understand the business problems and iterate through different analysis and results with them and finally come up with the insights and the conclusions and the recommendations for the business most of the times communication and storytelling will take place in form of presentation or documentation or emails or dashboards it's also the key to know how to ask the right question and finally on the top level I'd say we need some domain knowledge it gives you the ability to really understand the business questions and also better understand the data as well if you're working for buying or for trading platform you probably need to learn something about Finance this domain knowledge you can get from either your education background down all your working experience in the field there are many ways and resources to learn these skills I made another video earlier on my Channel about how to learn these skills fast with online courses in another video I talked about all the books I'd recommend for learning data science and there's also a lot of free lessons on YouTube and you can even use chat TPT to Learn Python and a lot of different skills which is also a great idea for self-learning as well for Math and statistics it can be quite easy to get into the rabbit hole and never feel like you've learned enough and for me after six years I can tell you I still feel the same way but it's okay to have the basic to intermediate understanding and a lot of things you can actually learn on the job so don't be too worried about not knowing enough for Excel I'd say you want to really Master it you want to know the basic things like the back of your hand things like vlookup index match conditional formatting creating pivot tables and you can go for more advanced things like macros and VBA to automate repetitive tasks and optionally power query also if you need to connect different data sources in the next few years I guess all of these small tasks can be easily automated with AI so the main competence we need is knowing how things work and if they work as expected it's much easier to ask help from captivity to write some VBA code for you if you know already how VBA Works a learning strategy I really believe in is transfer learning if you already know a programming language for example SQL or R it can be easily transferred to a new skill like python when I first learned python I often try to relate things from R which I was more familiar with for example if I want to concatenate two data frames at Google how to row bind data frames in Python because that's how I would interpret it in R also all the basic concepts like variables and data types and functions lexical scoping are almost almost exactly the same across different programming languages so over time you develop the intuition to know how to do things and problem solve and all the rest is simply practice when it comes to data visualization it's probably one of the most fun things for me to do as a data analyst this can be Standalone visualizations that you can make in r or python or Excel or in the form of dashboards or presentation for starters they are good books such as storytelling with data I also made a video on my channel to show you all the do's and don'ts in database so check it out for dashboarding you can learn it pretty quickly with some courses on Tableau or power bi I personally prefer Tableau over power bi because it's a bit more performance a bit more fun to work with but it's up to you for soft skills like storytelling asking questions and presenting you develop them over time but you can also proactively learn to become better at them by practicing it by writing blogs about your projects pitching the ideas and insights to your family to your friends to your neighbors and see what they think it's totally possible to teach yourself all these skills but if you prefer to have a clearly defined program with clear structure and timeline to work towards you can consider career foundries data analytics program this is a flexible four to eight month program that teaches you the mindset the processes and tools to become a data analyst you get paired with three dedicated experts in the field and have online lessons that go over all the basic concepts and Hands-On assignments you'll learn tools like SQL python Excel Tableau and GitHub for data analysis work it's a totally flexible program so you can do it in your own schedule there's no need to quit your day job or become a monk you book calls with your mentors at times that suits you and you'll get personalized written and video feedback throughout the program in this program you'll also have a dedicated course on job preparation to make sure you stand the best chance of getting a job there's also a slight community of fellow students who are taking the program so you won't be alone in this Learning Journey a really cool thing about this program is the job guarantee you get the job within six months of graduating or career Foundry will refund the cost of your program so I think this is an excellent option if you want a more structured and more guaranteed approach to transitioning to data analytics I think it's worth the investment given the promise you get so check out the program in the description below in a sea of candidates you definitely need to stand out and how do you do that I believe a good personal portfolio is going to be one of your Best Bets it helps you effectively showcase your skills and get the attention of the recruiters also for yourself it's a great way to put your skills to test and gives you the sense of esteem sense of confidence that's probably the most important aspect of it if you don't know what exact projects to do I talked about building a data portfolio in another video and there's also a lot of tutorial videos on my channel that take you step by step how to do them I put perhaps hundreds of hours into creating them so be sure to check them out you can adapt these projects or ideas to your target company or domain area for example if you want to work at the Healthcare Company you can analyze healthcare related data sets if you want to work for an e-commerce company you can try to make a sales dashboard and analyze customers behaviors Etc and for more ideas join my Discord server and here's some extra tips firstly be sure you have three to five projects in your portfolio I think for most of us the first one or two projects are going to suck anyway so I think three to five projects is a sweet spot where you actually make something good and diverse and interesting secondly do projects about something you care about find or create data sets that you are interested in and put some love into it your passion will show it's quite easy to see how much care and commitment someone puts into their projects and the third tip is everything is hot until you figure it out sometimes it takes a lot of courage to get over the mental block to even get started or continue a few months ago I started learning motoring yes I'm trying to be healthier but climbing also teaches me a lot of lessons about getting over my fears to fully commit to a difficult move I'd be so scared even though I know I'm not going to die from falling to meters off the ground but sometimes it's so hard so yeah I'm a bit of a coward but it's also very refreshing to know that I can train myself to think I'm scared but I'm going to do it anyway after having some skills and portfolio projects under your belt it's time to get yourself out there I find that offline Network like friends and relatives and former classmates or colleagues is the easiest way to find jobs maybe because this is what's worked for me before but there's also a lot of opportunities online I know many of you have good profiles and skills so I was thinking of how to connect you my audience with the job opportunities that I see I know from my employers and people in my network so I've made a small Google form Link in description if you're interested please fill in the basic details about your profiles so I understand what you're looking for I still need to figure out the details how this world will look like and there's no guarantee in terms of jobs but I do want to explore this idea further in the coming period so I can better serve our community LinkedIn is also a good place to reach out to people already in the field and recruiters I've never tried to reach out to Recruiters on LinkedIn but if you try it just be sincere in your email use proper language don't just say hey there you may double check grammar using grammarly or run it by a friend from my experience a common mistake which is also my mistake is to undersell yourself if you're really new in the field you may be tempted to say I just graduated and I'm still learning it may be true but it's not what employers are looking for you may want to frame it in a more assertive way along the line of what you have done and what you could contribute to the company based on that for reference definitely also make sure to send the recruiter an up-to-date resume that should include the links to your portfolio projects like GitHub repos or portfolio websites or other mentioning of your projects online also if you have any kind of connection to the company even the slightest like you attended an event by the company or talked to someone there bring it up if you have any previous working experience or some domain knowledge you should definitely leverage this even if you worked as a barista or cashier at the supermarket this counts as your domain knowledge data analysis is nothing without context without business problems if I were you I'd really mentioned these experiences and try to link them with the job I'm applying for try to tell a little story and show them what I have learned and that may benefit the company it's not always easy or straightforward but I think this is a very effective and clever strategy okay talking about AI there's no doubt that large language models and AI tools would transform analytical jobs at some level a recent analysis found that large language models such as GPT could have some effect on 80 percent of the US Workforce some creative and high paying jobs are most vulnerable are writers web and digital designers together with financial quantitative analysts and blockchain Engineers but I think overall the upsides are going to outweigh the downsides a very recent study showed that the AI tools helped the list skills and list accomplished workers the most decreasing the performance gap between employees so in other words using AI the poor data analyst will get much better and the good analysts will simply get a little faster as you probably already know data pre-processing perhaps takes 70 to 80 percent of the work for many data analysts and data scientists most of it is pretty tedious and annoying so I think tools like chat TPT and gpt4 can help us automate a lot of those tasks and simplifying and streamlining the data analysis process or perhaps dive into this in another video that being said there are certain things generative AI cannot do thankfully at least not yet even today's most sophisticated large language models still like the abilities like critical thinking strategic planning and complex problem solving nowadays it's not about simply doing the same thing for cheaper anymore companies really need to innovate and think outside the box if they want to stay in business so as a data analyst you have the power to help them to do this and also although interpersonal skills like building trust and relationships and telling jokes you can expect all of these aspects are where human data analysts can Shine the key for us is to keep on learning acquire good fundamental skills and stay up to date on how to utilize all these AI tools and techniques to be better at our job and also more than ever we want to focus more on soft skills like empathy and communication and relationship building I hope this video gives you a better understanding and a roadmap of how to transition from another field to become a data analyst you can find all the links and resources in the description below and if you like the video please smash the like button and let me know your thoughts below I love you all thank you for watching bye thank you

Channel: Thu Vu data analytics

Views: 170,906

Keywords: data analytics, data science, python, data, tableau, bi, programming, technology, coding, data visualization, python tutorial, data analyst, data scientist, data analysis, power bi, python data anlysis, data nerd, big data, learn to code, business intelligence, how to use r, r data analysis, vscode

Id: N1UMycRJbAw

Length: 17min 52sec (1072 seconds)

Published: Fri Mar 31 2023