Should You Still Learn Data Analytics? (in 2024)

in the late '70s Harvard student Dan brookln was sitting in class bought out of his mind little did he know his daydream about a magic Blackboard would give birth to digital spreadsheets waving goodbye to paper spreadsheets this invention later evolved into what we now know as Exel the Swiss army knife of any data analyst today the software that holds the business world together in the past 40 years one sale at a time now fast forward to 2024 with AI coming into picture this year 2023 alone has seen gbd4 and Advanced Data analysis GitHub co-pilot adding loads of new features AI assistant framework for self-operating computer Microsoft AI agents Microsoft co-pilot Gemini and loads of open-source models coming to life recently I've heard a lot of you express concerns and worries about the future of careers in data analytics and data science is learning data analytics still worth it is it still a viable career let's say in the next 5 years the answer isn't as straightforward as you might think and with this video I hope to share some thoughts and ideas to help you make up your mind a quick shout out to today's video sponsor corer who is running an exciting offer more than later looking back data analytics has come a long way back in 2016 when I started my data analyst job at the time very few people really talking about Advanced analysis machine learning or deep learning most companies were still struggling to figure out what the hell to do with the data you might have come across this data analytics maturity curve some companies are still just struggling to even understand what's going on in the business some are more ahead and already have the infrastructure to gather the data and already start building predictive models an overwhelmingly common reality no matter where your work lies along this curve is that you've got to spend a big chunk of your time on anything else but data analysis even in a machine machine learning project you spent like 7 to 80% of your time cleaning and pre-processing data patching data from different sources together rather than doing the creative data detector kind of work that aside when I finally finish some analysis and want to show some graphs my graphs often looked awfully ugly and I would stay late at night tweaking the labels and AES on the graphs the rest of my time would be spent rushing to write a documentation for the project which is by all means the most boring t ask so I realized that this is really not as sexy as I thought and what does the job of data analyst or data scientist today look like how me clean this data set using the following steps please make the bars have the same color and the title The Boat what a time to be alive with AI tools I I genuinely believe that this is going to give data science jobs the chance for real to be truly sexy imagine this AI does the grun work and all the boring tasks and you the savy data analyst tackle the creative complex problems interpret the results and recommend actions for the business you're like the shlock hommes of data I don't know about you but this is what I would think of as a sexy job by the way if you're a complete beginner and looking to gain a certificate in data analytics to jump start your career coera is running a discount with $200 off the corer plus annual subscription if you sign up this is half the regular price for the whole year if you consider getting this subscription you can check out the link in the description below to get the $200 discount this subscription is 14-day money back guarantee so if you sign up and you don't like it you can cancel it within 14 days with this subscription you can get access to tons of courses and certific ific Ates in data analytics including the Google data analytics and the Google advanced data analytics certificates these certificates teach you all the fundamentals you need as a beginner in data analytics so check out the offer below now let's talk about the elephant in the room will AI replace data analysts can it fully automate our jobs it's not so black and white economists believe that automation does two opposite things simultaneously it still tasks for from humans while also creating new tasks for humans and since a job is a collection of multiple tasks automation eventually changes the task content of a job as we just mentioned earlier the repetitive and routine tasks like querying data cleaning and simple exploratory analysis can now easily be done by gbd4 so human analysts can now focus on the more creative more nuanced tasks that require deeper understanding of the world and the social skills to me it seems like AI won't fully replace analysts in a foreseeable future but human analysts will need to learn to collaborate with AI to optimize his job just like the invention of digital spreadsheet didn't replace accountants it transformed them since the release of Microsoft Excel the number of bookkeepers and accounting clerks has dropped significantly however the number of accountants Auditors and financial managers has generally increased the big really big Accounting Service firms like the big four companies are still thriving rather than going bankrupt yesterday that's why I still get to keep my day job but let's not paint an overly optimistic picture the effect of AI automation on jobs is still not yet clear it all depends on whether the new tasks that get created outspace the old ones or the other way around a research paper that studies the effects of Technology on labor demand points out that but in the four decades following the World War II there was plenty of automation but this was accompanied by the introduction of new tasks so labor demand was not decreased due to technology however over the last 30 years labor demand growth has actually slowed down this is due to the consistent productivity growth thanks to the rapid Automation and Ai and also that the loss of labor intensive task has not been counterbalanced by the creation of new task this is a very interesting research paper and it actually surprised me I've linked it below if you're interested reading the question is will this General pattern also apply to the data analyst jobs personally I think less likely millions of companies out there have never been able to utilize their data properly and still vying for analysts who can come in and use the data or at least figure out how to do that in a smart way with AI for larger larger companies that already have the infrastructure in place to really utilize data well they will still find it hard to automate data jobs from my experience any jobs around using data are usually subject to a lot of ethical issues data sensitivity data privacy issues so there are a lot of things going on rather than just number crunching these topics are only getting more and more important and more complex in the future so to be honest I think at least in the next 3 to 5 years I don't see how all these different aspects can easily be automated effectively with the AI tools that we see today however I do believe that we will see Less jobs that only focus on number crunching like data cleaning writing SQL queries kind of jobs and more jobs that require more high level skills from coming up with the business use case for data connecting different pieces information together from different sources draw insights and drive actions for the business knowledge on data regulations to make sure your company is not getting in troubles coordinating different analysis efforts and communication with stakeholders and tell a compelling story with data this leads me to another Point domain expertise is going to be very important data jobs are valuable not because we use fancy machine learning techniques or programming tools but because of the business value that they create data analysis is nothing without context data analysis is just a means to an end so I genuinely believe that domain knowledge would help tremendously with finding your place in the job market or in your current position even when technical skills like programming and data analysis are going to be automated away so if you happen to be in the middle of a career that's totally unrelated to data analysis I think this is going to be one of the best times to acquire the data skills I've met lawyers who jumped into learning about data privacy and AI regulations and became EXP experts in this field I've met GPS and doctors who became experts in using public health data to do analysis and raise awareness in certain Healthcare domains I've also met someone who works in a concrete production company who created machine learning models to find the formula for the best concrete mix so it's really fascinating how valuable domain knowledge can be so don't take for granted any work experience and knowledge that you got somewhere else sometimes it can be your best best selling point for career in data analytics today one problem you may face as a beginner is to learn all the basics in data science you may also be a bit older and going back to college is not really an option anymore but the world is very different today I feel like AI is lowering the entry barrier for beginners in data science things that took years to learn in the past at least in my case for the basics of programming some machine learning and deep learning now takes much less time thanks to chat TBD hello there it seems like you might have a question or something you'd like to discuss yes I have a question um what is a Lambda function in Python a Lambda function in Python is a small Anonymous function defined with the Lambda keyword it's useful for creating simple functions on the fly without needing the usual death keyword and function name and not only is fast as to learn the theories but also so the AI tools can help you very quickly build a data analysis project for your personal portfolio you can scrap the data faster coat faster solve problems faster present the results much more nicely so it's just generally much easier to create an impressive and interesting project nowadays with the help of AI a study showed that AI tools help the least skilled and accomplished workers the most decreasing the performance gap between employees so in other words the beginner data analyst will get much better and the more seasoned analysts will simply get a little faster if you're not sure where you are with your level you can quiz your skills with chat to understand what you are still missing I think today is very hard to say I don't know where to start anymore as a beginner also I think it's hard to find an excuse for having a bad resume if you can improve it or rewrite it using chat TPT in just 10 seconds so all know I see a lot of opportunities for entry for beginners in data analytics especially when the role of AI in a data analytics team today is not yet established companies are still finding ways to adopt the technology and Playbook is not yet available regulations are not clear and above all the AI tools are also not yet grounded or reliable enough to replace human analysts fully so looking ahead in 2024 is learning data analytics still worth it I'd say yes I still encourage you to get into data analytics if you enjoy working with data and making a difference in the world with your skills the jobs might look very different than they are today just like comparing today's data analysis tools with the first spreadsheets but I believe the job will only become more interesting the key to thriving in this career is adaptability asking if it's still worth it it's like asking if it's still worth learning to drive when self-driving cars are around the journey is half the fun and the destination Limitless possibilities thank you for watching and see you next video [Music] bye-bye

Channel: Thu Vu data analytics

Views: 122,513

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: JTHyfv_GUCw

Length: 12min 40sec (760 seconds)

Published: Sat Dec 30 2023