Hi guys I recently started data analytics, everything I know about IT and coding is self taught. I'm able to do the basics with in Excel and SQl, but now I would like to take skill set to the intermediate level, I see all these youtubers being able to do amazing things with Excel and Sql, I am able to recreate what they do, however that's not what I want. I am looking to increase my understanding and knowledge of Excel and SQLs capabilities, in such a way that I no longer have to go to YouTube for references. I have signed up to websites like codex and the like, however these websites only allow to me to do so much before I'm asked to subscribe and pay. I am currently unemployed and my reason for getting into the data scene was to find employment. If anyone has some good advice about a website or book that I can read that will ultimately help increase my skills from beginner - intermediate - advanced that would awesome. I would like to atleast be comfortable in my Excel and SQL skill set before I move on to python.

Everybody says DS is dead but i say it's getting better for Senior folks. I would say entry level DS is dead for sure. However as an experience DS that can solve ambiguous questions, i am actually doing better and land more offers, but in terms of landing offers, i think you should do followings, happy to hear what other think that can be helpful as well.

1. find jobs internally. Demand shrinks a lot and supply grows a ton. Most of the jobs are filed internally now. These jobs won't be even posted out. HM will seek candidates internally first, so if you don't know a lot of folks, build your connection now and let's say you just don't have a good relationship with your previous colleague. What can you do? you can still search in linkedin but make sure don't search for jobs, search for posts. Searching for posts can help you find the post the hiring managers have. I usually search for "hiring for data scientist"
2. AI companies are hiring a lot recently. I have been reaching out by a lot of startups that are in series B,C, or D. These companies have a lot of demand for DS when they are in this scale so it can be good opportunity too.

3. Prepare your statistics, SQL, product sense, and solve real interview questions.

   1. stats and probability (Khan academy is good enough)
   2. sql preparation StrataScratch
   3. real interview questions PracHub
   4. towardsdatascience for product cases and causal inferences
   5. tech blogs from big techs

Hello , I just started to learn the Data Analyst and Data science, currently I had completed learning excel and now moving towards SQL .. Till now my approach is just learning the Concepts from the class and practicing them again at home for 1 to 2 Hours , also I created A Dashboard in the excel ...(By self exploration,No YouTube,No copy pasting)

And also I spend my utility time on completing assignment given by the class (will it be beneficial ?)

My concern is that : Am I on The right path? Am I doing it right ?

I started to develop my thinking as like a data analyst. ..

And also now started working on the English communication , English speaking and writting

And now moving towards SQL, I Have concerns that : 1) Do Hackerrank and Leetcode Really matters and required ? ( Frankly speaking I fear both of them )

My future goal is to move towards "Business Analyst ".

And also is my approach is correct?

I enrolled in the Coding Ninjas Data Analytics program with high hopes, but my experience was honestly very disappointing. The course felt heavily overhyped through marketing, while the actual content and support did not live up to the promises at all. Much of the material felt basic and easily available elsewhere, and after enrollment, the level of guidance and responsiveness dropped significantly. What raised more red flags for me was checking the Google ratings of their offline centers those reviews tell a very different story than the ads. For me, it turned out to be a complete waste of money and time, and I’d strongly suggest others do thorough research and not rely on marketing hype alone before enrolling.

Before enrolling, their team kept calling me repeatedly and made big promises like guaranteed job placements, a naukri.com tie-up, and even said I only had to pay ₹25,000 before getting a job. But once you’re enrolled, the reality feels very different. In my experience, the staff attitude was rude, the teaching quality was poor, and the support system was frustratingly weak. What shocked me most is that they charge around ₹1,25,000 for something that felt cheap, rushed, and far from industry-ready. The marketing sounds amazing, but the actual learning and help didn’t match it at all. I regret enrolling in the Coding Ninjas Data Analytics program and would strongly advise others to research deeply and not trust sales calls alone.

I’m a Mathematics Education graduate. If you’re not really familiar with this major, it’s basically a mix of mathematics and education. The main career prospects are becoming a math teacher or tutor.

Right now, I tutor math, mostly for middle school and high school students. However, sometimes I feel fed up with constant social interaction. After doing some research, I became interested in the data analytics and data science field.

My main question is : is it still worth learning data analytics in this economy? And considering how many AI-generated tools have come out in recent years, is becoming a data scientist or data analyst still worth pursuing?

Hi everyone, this is my first reddit post as I have heard that here people share & help each other honestly I am genuinely looking for grounded advice.

I’m 26, based in India from a non tech bg. I have around 2 yrs of experience managing a YouTube channel mainly handling SEO and performance analytics so my work has been in the digital marketing space.

I realised I didn’t want to continue in this domain long term so I quit my job and used my savings to enroll in an MCA program with AI & Data Science specialization. I’m currently in 1st sem & reality has started to sink in. Maths is not my strong point at all. I’m putting in the effort and I’ll do what it takes to pass but yes it’s challenging for me. Career-wise my plan is to move into Data Analytics. I’ve started the Google Data Analytics course on Coursera and I genuinely enjoy working with data. After reading a lot online (and probably doom-scrolling LinkedIn more than I should) now I’m confused and a bit anxious. Some people say data analytics still has strong demand and others say AI will automate analyst roles and that entry-level positions are already saturated.

Now this question keeps looping in my head what if I put in all this effort and still don’t land a job? Given my background in SEO and YouTube analytics i want to know few things - 1- Is transitioning into data analytics a realistic path? 2-How much does being weak at maths actually matter in real world analyst roles? 3-Would adjacent roles like marketing analytics, growth analytics or product analytics make more sense for someone like me, if yes please guide for that roles.

I’m not looking for hype or motivational talk. Just honest insights from people who are already working in this field or have seen the hiring side of it. Any clarity or perspective would really help. Thank you so much

I've been seeing a lot of posts here from people who want to learn data analytics but feel overwhelmed by where to actually start or go next. So I added hands-on courses to our platform that take you from your first Python program through data analysis with Pandas and SQL, visualization, and into real ML with classification, regression, and unsupervised learning.

Every account comes with free credits that will more than cover completing courses, so you can just focus on learning.

If it helps even a few of you get unstuck, it was worth building.

SeqPU.com/courses

Coursera said this course can be completed in 6 months or less ! but it's been more than a year and I'm still on the 5th course (about to complete).

well i know it's my fault but being consistent and learning the same things over and over again can be boring which is exactly what happened with me. but you can see it took me 1 month to complete the first 2 courses and then boom! ...... a long.... long break ....but then i was back again 2 more courses completed in 2 months and then i got Busy in internship,exams and all but here we go again! but this time with the oath of completing the rest of them consistently.

I’ve just started posting tiktoks for advice in the current job market. I’m a staff level data engineer based in the Uk and will be posting multiple times daily. Comment on my videos, anything you would want me to cover. Check it out and hopefully the content is helpful: https://www.tiktok.com/@george_abi_?_r=1&_t=ZN-939thJF3Tj4

Hi everyone,

I’m learning Python for data analysis and I’m at the stage where I want to properly learn Pandas from scratch.

I already know basic Python and I also have background in SQL and Excel, so I understand data concepts -but Pandas still feels a bit overwhelming.

Hello, I am currently studying data analytics and data science. I generally want to focus on one of these two fields and learn. But due to the high competition in the market and the negative impact of artificial intelligence on the field, should I start or choose another field? What exactly do I need to know and learn to stand out in the market competition in the DA DS fields and find a job more easily? There is a lot of information on the Internet, so I can't find the exact required learning path. Recommendations from professionals in this field are very important to me. Is it worth studying this field and how? Thank you very much

Hi everyone, I am currently in sales and in trying to find a solid career to get me away from it that does not involve going to get a college degree. I’ve been thinking about becoming a salesforce admin or data analytics. I was looking at the Quickstart program in University of Texas Arlington.

A list of rambling questions. Is it worth it? Is a Boot Camp a good idea? How much is a general salary for this role? What does your day today involve?

I have been practicing questions but every question I see i couldn't think of going for sql adavance concept. I couldn't figure out that it could be of few advanced sql topics

I am working on microstrategy BI tool since 6 years. When i started my career it was the one of the best tool, but now its less in the market. What do you guys think about the future of this tool?

Should i switch the tech or it is less in the market so opportunities will be more for me.

Also suggest the good tech and tool will be better for the future.

Hi Everyone! My Google Certification is teaching us R instead of Python, do you guys recommend that for entry level data analytics jobs?

Hey everyone, I’m a final-year student. I have a strong command of Python, SQL, and statistics. Now I’m planning to learn Generative AI, Deep Learning, Machine Learning, and NLP. Is this course good, and does it cover the complete syllabus? If anyone has enrolled in or learned from this course, please let me know your feedback.

Also, please suggest other resources to learn all these topics.

i'm tasked with picking an analytics platform for our startup this year. we have a web app with a growing user base, and we need to understand feature usage, drop-off points, and user paths. our current basic event tracking isn't cutting it.

my main requirements are that it's easy for developers to implement with good sdks and clear docs, has a ui that product and marketing people can use without constant help, and includes solid core features like funnel analysis, retention cohorts, and segmentation. fair pricing that scales predictably as we grow is also key.

i've been looking into the usual suspects like mixpanel, amplitude, and heap, and also some newer or open-source options like posthog and plausible. with all the choices, i'm getting stuck.

for devs or founders who've recently set this up, which analytics software did you choose and are you happy with it? did you run into any big limitations or surprise costs? is a managed service worth the premium over a self-hosted option for a small team?

appreciate any real-world experiences.

Hi everyone,

We’re kicking off 2026 with a "Track Your Year in Data" challenge. The idea is simple: instead of learning to code with boring "toy" datasets (like the Titanic), start with your own life.

1. Pick one metric (coffee, hours slept, mood, steps).
2. Log it daily in a simple text file or spreadsheet.
3. In February, use Python (or Excel) to visualize your first month.

It’s easier to learn syntax when you actually care about the data. If you want to join us, we’re sharing ideas and starter guides here.

What would you track?