So to summarize, with some stats from searching on Indeed with the title and country set to the United States. I checked the first page of each if they had the correct roles posted. Core data roles: 1. Data Analyst - 22,375 jobs 2. Machine Learning Engineer - 15,644 jobs 3. Data Engineer - 7,655 jobs 4. DBA - 3,664 jobs 5. Database Developer - ? (searching "SQL Developer" listed 1,923 jobs.) Dying roles: 1. Data Scientist - 10,919 jobs 2. ETL Developer - 5,449 jobs 3. BI Professional - ? (searching "Business Intelligence" and "BI Developer" listed 5,928 jobs and 5,494 jobs respectively.) Note: ? is because too many irrelevant results were coming up when searching for the role on the first page itself. So I wrote in parentheses what I think is the closest alternative, which returned much more accurate results. BTW In the new Google certificate, BI Analysts and BI Engineers are presented as the two main BI roles, not sure if this reflects reality or not. I didn't provide stats for these either due to the same issue of irrelevant postings when searching for their title.
I will be re-joining LogikBot to revisit the feature engineering course, seriously Mike, that course is a masterpiece, taking alone will put you above 99% of the crowd, it's that good!
Great video! I have been religiously following your advice. I wish I could say I was part of the subset of people who complete your courses and go on to get a Data Analyst role but my current (new) IT support job has taken priority in the last few weeks. Can't wait until I free up the hours needed to get properly stuck into your material Mike! So helpful for people like myself who aspire to become very competent in the area of Data Analysis and make an impact in that sphere. Thank you so much for putting these vids out there. It really helps "dunning kruger kids" (like what I used to be, now in recovery from that idiocy) sort out their worldview when it comes to the data space. Good job!
Well I am a Da Engineer, who never worked as DBA. I was a an overskilled technical support and then switched to a Data Engineer type of job in on-premise ecosystem. It was a hard switch and hard to get the job in the first place but I managed. I had also advantage of advanced german language, which definitely helped me then (and still does)
I enjoy the direct nature of your videos (I've binge watched many) and although I mostly agree with you, I do feel that you somewhat oversell SQL and neglect to talk about the importance of software engineering fundamentals for DE/ML roles. What's your opinion that data engineering will start to split into two different "roles" in the future: Analytics engineer (Heavy SQL, data warehousing, close to business, etc.) and Big Data Engineering (Heavy programming, dev-ops, kafka, spark, further from business etc.). I've been a DE for the past two years and, outside of DDL statements, haven't put much SQL into production. IMO the most rewarding elements of DE is this dev-ops/ micro-services work, so I am curious to hear your opinions on this topic. Thanks!
The roles are fairly well cemented. Again, I've worked at Uber and Microsoft and I keep in contact with a ton colleagues there and they all agree with this video. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-5iPgpad37x4.html
Hey Jimmy! As of now I am in my second year of my undergrad course of engineering and have done bs certifications etc. How do you think I should proceed to get closer to data roles? What did you do during your undergrad?
2:08 - (When talking about Machine Learning Engineers) ...they build the models 3:50 - Machine Learning engineers ... don't code their own models What is the difference between 'creating' models and 'building' models, in this case?
Creating a model means writing all the code for the model. Here, I wrote this simple linear regression model from scratch. qr.ae/pvbaH7 When we build model we use libraries and frameworks like TensorFlow and PyTorch for deep learning and XGBoost for traditional modeling. These are already written. We simply pass the data into the model and it provides us with a prediction.
I have a master's in data science. In the class I took on mySQL, the instructor said we would qualify to be DBAs at the end of the course. I was dubious of the claim even then. He has a PhD, so...
LMAO. Most professors are full of shit. If they were any good at what they were doing they'd be working in the real-world making three times what they are making now.
Hi Mike. Do you think job titles matter? For example, what if someone does the job of a Data Analyst but their title is BI Analyst. Is that going to matter when applying for any future roles?
Hell yes it will. If you're a data analyst and you're interviewing for a BI role and can't define how a decision tree works the interview is over and you just lost that job. If you're a data analyst and have never done any data mining how in the hell are you going to answer the data mining algorithm questions in the tech interview? At real companies titles matter.
*My students are learning the right skills? Are you? (No, You aren't) TRUST ME. YOU'RE CLUELESS.* SUMMER SALE. Use the code JULY at checkout to get 3 months for $40. That's $14...ish a month. Affordable and real-world. Stay clear of roles that aren't going to help you. If you want to be a data analyst then I have you covered. www.logikbot.com. < It's all there. The SQL course. Then the PowerBI course. Then the exam simulator of passing PL-300. All you need to do is sign up and learn. Additionally, it's the most affordable real-world path that exists.
I am in the process of becoming a DA. What is your take on a the WGU BS Data Management & Data Analytics degree? I'm encouraged by your advice that all DA's do is make dashboards and KPI's and after my move to Washington, I'll use LogikBot, but many roles require a bachelors degree. Would you recommend the WGU degree as a supplement to your courses? I am in a position to where I am not in a hurry to get a DA role and would like to get the BS (double entendre intended) out of the way
All data analytics degrees are a waste of time. No real-world skills are taught in college. Focus on SQL and a tool like PowerBI. Now, you *do need a degree* but no one really cares what that degree is in and comp sci degrees don't give you any extra credit on your resume. Companies want skilled candidate with the tech they are using.
Hey Mike, alongside data engineering, I often hear the term “Data integration”. Is Data integration just another niche within data engineering or is it a separate field?
For logikbot, do you have a structured outline/pathway for someone new to follow? Like a guideline on the order of courses to take? There a so many courses, It will be so helpful. Thanks!
The only role you should be taking is the data analyst role. It's simple. You take the Transact-SQL course and fill in the interview preparation. Then you study that guide until you know every SQL question on it. Next, you take the data analyst course. You learn as much about PowerBI as you can. You then study for PL-300 using my exam simulator. You then sign up and try to pass the exam. That's it.
Hey as someone who has and does work with data in the real world, is the role of the DBA disappearing or the number of roles decreasing for this position? I've heard/read that this role is disappearing as more companies move their operations to the cloud.
Nope. No Projects. Watch this video. ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-IVIUO_aE_0E.html You need skills... SQL and a tool like PowerBI or Tableau.
@@thedatajanitor9537 Is there any video you made or can you please make a video on how the resume should look like for applying to a data analyst role (No experience, fresher)
Would majoring in Statistics & Data Science at UT Austin limit my career beyond a data analyst greatly? It works better for me logistically than majoring in Computer Science but I'm afraid it won't be as useful. On the other hand, it seems like the computer science major would make me spend a lot of time learning stuff I'm not super interested in like computer architecture, coding in C, etc. I initially was drawn to Data engineering but now I'm considering data analyst and eventually moving into BI. What do you think? Would getting a masters in Computer Science after also help?
You need to watch my videos Colby. BI is dead. It's been replaced with machine learning. You have three top tier options in the data space. The DBA, the data engineer and the machine learning engineer. The data analyst is not considered or treated in the industry as a top role.
Im messin with logikpro but i was in barnes and noble today and stumbled past data science for dummies ended up ordering it on amazon prolly a waste of read of why not I thought, what do you think?
Yep. A waste of time and money but you can always return it. Data science is a dead role. Here you go: ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-8ttGzR2U57A.html
What about NLP analyst or Engineer been seeing these around since mid 2022 now they are "HOT" due to ChatGPT, where do these people live in this spectrum ? Also what about image processing and Aiding is it truly only AI or math it's so confusing to me
No such thing as an NLP analyst. There are machine learning engineers that specialize in NLP and deep learning. They are still called machine learning engineers and while cleaning data is a little different, they still spend most of their time cleaning data. All of these models are called "generative" Ai models and they are all deep learning. These roles are insanely hard to come by and most of them are hardcore programmers.
Hey Mike, i’m doing my undergrad in a couple of months and I hope to be a MLE one day. Should I just solely focus on studying to become a data analyst first and is there anything else i can do/study within these 4 years to help me in the future? Thanks
You addressed it to Mike, however here's my take. If your undergrad is in tech...hurray, you get to learn a lot, databases, programming, etc. If you put in some good effort plus summer internship, you should be skilled with the required sql for entry level job. Then you do tableau or power bi. If your undergrad is not tech related, you can get started with databases, either self learning or buy a good course. You should have some programming skills if your end goal is mle. If you plan your education well, you should be marketable right after sch.
Hello Mike I am going to take your courses but I wonder how hard it's to get a remote job out of the US as a data analyst because there aren't that much entry level role in my country
That just doesn't happen, you need a visa before you apply even for a remote job. The only time it happens is when you are exceptional talent they cannot find locally, which is extremely rare. In that case they would be reaching out to you rather than you applying anyway
would just say that you can be paid like a freelancer or they will outsource but you won't be someone who's working in the US Dunno about legality of it but many jobs are like that in LinkedIn and got friends who did that for like a year or two for extra cash
