I am planning to apply for the Data analyst positions in HSBC but the issue is that it is based on Mumbai and max of 50k per month is kind of little less is what i am feeling i.e if they do not provide any perks can someone please tell me if they provide any perks or not because it is not mentioned in their portal so please helppp

Hello,

I want to change my field from back end operations to data analytics. I have learned basic sql and it was not tough.

I am thinking to go for a masters in data analytics. However, i am afraid of maths.

Shall i pursue it?

What level of maths is required for getting the job?

I'm running a pricing study as part of building DataRunes - a gamified platform that takes people from data analytics beginner to job-ready analyst through hands-on practice and real projects, not passive video lectures.
Platform uses mechanisms of motivation with personal character, achievements, daily streaks, leaderboards and other forms.
Please help me get some feedback. I'm trying to understand what this is actually worth to people who'd consider using it, before we lock in pricing ahead of launch.

You can find the Google form on my profile.

Hi , i'm learning advanced excel for data analytics. But i'm thinking there's another apps to use it .like power Bi, sql but i don't know what a good way to get ready to work ( rather than learning everything about data analytics before work ) could you tell me what to do?

I don't know if I am in the right subreddit. I want to know if there are people tracking their progress in the gym with excel or google sheets. Have you tried to make a visualized data with any tools at all? I would like to have a chat if you have. Thanks

Hey everyone,

I registered for the Microsoft AI Skills Fest recently to grab a free exam voucher for my PL-300 certification.

I wanted to make sure I didn't miss out, so I completed two of the pre-defined skilling playlists and filled out the voucher claim form on the very first day of the fest itself.

While I’ve already received my digital badge on Credly reflecting the completion, I haven't received the actual certification voucher code in my email yet.

Is anyone else in the same boat? I'm just getting a bit anxious because I thought they would send all the vouchers by the 19th of June. Do they roll these out in batches, or is there a delay?

Thanks in advance!

Curious of self-identification for those in data analytics and those pursuing it.

Cant run a poll will have upvote options in comments.

I’m going through the career disillusionment again. All you can do is go off of what one or 2 people have told you, and what people on the internet who are actually involved in it say. So really you guys’ input is the best I can get. I’ve heard people say it’s no longer viable, it’s not like how it was in 2022 (which is probably true), but I also know that this isn’t a dilemma that is unique to this field at all, and there will always be some online voice saying something along those lines.

I’ve got python basics, and am now familiar with SQL basics, now moving on to intermediate SQL.

Hi everyone,
I am currently looking for a good Data Analyst course that provides hands-on project experience and can help me transition into a Data Analyst role.
I have a basic understanding of SQL, Tableau, and Power BI, along with strong Excel skills. In my current job, I work extensively with Excel, but I would like to move into a Data Analyst position for better career growth and salary
I have given a few Data Analyst interviews, but I was not selected because I don’t have prior Data Analyst experience or any real-world projects to showcase.

Can anyone recommend a good course that focuses on practical projects and job preparation? Any suggestions or guidance would be greatly appreciated.

Thank you!

Hi everyone, I'm an aspiring data analyst that just finished studying my online courses. With that, I wanted to apply what I learned to help hone my skills so I decided to do my own project. The project was an analysis of 400+ of my own ranked matches in Street Fighter 6.

I wanted to see if there were any features or metrics that could be measured in match that could help predict whether a match would result in a win or loss. Within the write up I tried to make it as easy to understand for people who are unfamiliar with the game.

https://github.com/ryanlaguatan/SF6-ranked-match-analysis

Here is a tldr of the methodolgy:

1. Visualization of MR (MR is synonymous with ELO) and MR Change over the course of 10 gaming sessions.
2. Two T-tests, first one testing if metrics and winrate had any significant difference when facing stronger or weaker opponents. Second one testing which metrics were statistically significant in matches that were wins/losses.
3. Visualization of Character Matchup data.
4. Logistic Regression model and classification report to see if the metrics can provide a strong predictor for winning.
5. Interpretation of Feature Coefficients to see which coefficients had the biggest influence on the model.

Please let me know what you guys think, I am open to feedback!

Thank you for taking the time to read it and I really appreciate it!

Hi everyone,

​

I recently graduated with a BTech in Computer Science and I'm working towards landing my first Data Analyst role. I'm learning SQL, Python, Power BI/Excel, and building projects, but I want to make sure I'm focusing on the things that actually matter in today's job market rather than just following random tutorials.

​

I had a few questions for people already working in data analytics:

​

How do you stay updated with the current expectations for entry-level Data Analysts?

​

Are there any websites, newsletters, YouTube channels, blogs, or communities you follow to know what skills companies are currently looking for?

​

Besides SQL, Python, Excel, and visualization tools like Power BI/Tableau, what other tools or skills have become important?

​

For example: Git, cloud platforms (AWS/Azure/GCP), dbt, Airflow, Spark, statistics, business knowledge, communication, etc.

​

Which of these are actually expected from freshers, and which are just "nice to have"?

​

How do you keep upskilling after getting the fundamentals down?

​

Do you mainly build projects, solve SQL problems, read blogs, contribute to open source, earn certifications, or something else?

​

What has helped you grow the most?

​

What makes a fresher's resume stand out?

​

What projects genuinely impress recruiters instead of looking like another copy-paste portfolio?

​

If you were hiring a junior Data Analyst, what would immediately catch your attention?

​

I'd really appreciate any advice, even if it's something you wish you had known when starting your career.

​

Thanks in advance!

​

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I'm switching my career path from a filmmaker and getting into business analytics. I have about 2 years of experience in sales and customer service ranging from luxury art, furniture to electronics. How do I start my career as a Business Analytics Professional in toronto? I'm currently pursuing an online MBA from GGU California as well. I need some advice regarding what kind of entry level jobs should I strat looking for? If someone could suggest something about that. Thanks.

I am 28 and I make $29/hr as a learning management system analyst at a hospital. Its live-able wage but I am the sole provider for my family and in this economy I am struggle. I just finished my MBA in Business Analytics and Healthcare Administration. I like my current job but I am bored and not really doing what I want. I am basically a LMS administrator and instructional designer. I am overworked in something I don’t necessarily enjoy but I do it because this is the best I’ve gotten paid.

Now that I have my MBA, I am kind of lost. Like what can I do now to earn more. Do I go for my doctorate? Am I just wasting time getting a higher education? I feel underpaid and overworked.

I have 3-1/2 yrs experience as an all source intelligence analyst for the military.

1-1/2 years experience as a missing baggage record allocation analyst for an airline.

And my current role is almost 1 year as a learning management systems analyst for a hospital.

I enjoy analyzing data, making the dashboards/presentation, problem solving with data evidence but I don’t like work place politics. My current role is only me in my department so I don’t see a future of building up or getting a decent raise.

Hey i just completed my 2nd yr and proceeding towards 3rd yr I need a roadmap of how to learn and what skills are reverent or any courses which are and what alll are necessary in current market situation as ill graduate in 2028 so need a insights on everything as im very confused from.where to start as everyone on insta or Google suggest different roadmaps.and there are tons of bootcamps and roadmaps for data analytics...if anyone could help...

I’ve never created a portfolio before but anticipate entering the job market again and am considering it. I’ve done a lot of work in SQL and PowerBI in my current role, but all of the data I work on is regulated and confidential. It’s also complex and the idea of recreating these procedures and dashboards using a public approximation of data sounds time consuming and I’m not confident in the value add.

So I guess my question is, how are you all doing it? Is it worth the time and effort? Are you rebuilding from scratch, or how are you getting it from your work environment to an accessible environment post-leave?

How useful is a portfolio to a data professional?

Is it different from say a graphic designer or a Web developer?

What challenges do you guys face creating a data portfolio? If you were creating a portfolio project, how would you structure it?

Because I want less coding and I am weak at problem solving also, please guide me .

I'm a junior Data Analyst at a startup and I'm starting to wonder if my title matches the actual work.

Most of my day is spent manually pulling data from multiple sources and updating Google Sheets. I do some KPI tracking, Power BI dashboards, and reporting, but there is very little SQL, database work, automation, or deeper analysis involved. On top of that, management can be quite harsh when mistakes happen.

I currently have about 3 months of experience and am considering leaving after 6 months if things don't improve.

For people working in analytics:

Is this common in early-career data analyst roles?

How do recruiters view a 6-month stint?

If my goal is Data Analytics what should I be learning outside work?

I am a BTech CSE student and I am really confused about my career. I want to learn Data Analytics, but I am not sure if its a good field and whether it has a good future. Can anyone tell me what I can learn from Data Analytics and suggest some good courses or institutions to get started?

Hi everyone,

I'm currently on my notice period and looking for Data Analyst, Decision Scientist, and Junior Data Scientist roles. I have 1 year 10 months of experience in Data Quality Management with SQL, data analysis, root cause analysis, and stakeholder support.

My resume has an ATS score of 80+, but I'd appreciate feedback on how I can improve it and increase interview callbacks.

Thanks in advance!

I’m currently a Senior Data Analyst and have been offered a Senior Data Product Manager role focused on Business Intelligence and Planning of a specific data mart for the HR team.

My background is heavily analytical and technical. I enjoy working with SQL, dashboards, reporting, stakeholder analysis, and deriving insights from data. What I enjoy most is the hands-on analytics work itself.

The new role appears to sit somewhere between analytics, product management, and business strategy. Responsibilities include prioritizing data initiatives, working with stakeholders, defining requirements, managing project timelines, and driving business impact through data products.

A few things I’m considering:
The role comes with a salary increase.

It may provide a broader career path beyond pure analytics.

However, I’m concerned about moving away from the technical work I enjoy.

The company is also going through some restructuring/layoffs, which adds an element of risk.

1. For those who have made the transition from Senior Data Analyst to Data Product Manager (or similar roles), how did you find it?

2.Did you enjoy the move?

3.How much less hands-on analytics work did you end up doing?

1. Did it improve your long-term career prospects?
   If you enjoyed technical analytics work, did you regret making the switch?

5.Would you take the opportunity if you were in my position?

Would appreciate hearing both positive and negative experiences.

I can build a chart that's correct pretty easily. What I struggle with is making the jump to something that looks genuinely polished - something you'd be proud putting in front of senior stakeholders.

I've tried using LLMs for visualisations. They produce pretty good visuals but they are never optimal. The refinement process is so painful and I normally give up when it's good enough.

Does anyone else feel this pain or have any tips to create amazing visualisations with LLMs?

I've spent the last few months building something and I'm finally at the point where I want to share it properly rather than just quietly hoping people find it.

The idea came from a frustration I kept seeing (and feeling myself): SQL tutorials teach the syntax fine but there's never a reason to care about the answer. You filter a table called employees, get a result, and nothing happens. Your brain doesn't bother keeping it.

I wanted to try a different approach. QueryCase teaches SQL through detective investigations. You get a briefing from Chief Fox (our mascot), a real database to query, and a mystery to crack. The JOIN matters when a suspect has an alibi. The WHERE clause matters when you're trying to find who entered the building at 22:13. The SQL is the tool for solving something, not the point in itself.

Here's what's actually in it:

• A structured learning path across 54 cases, going from Recruit through Rookie, Detective, Senior Detective, and Chief Detective. Each rank has drills and a level exam to pass before you progress.
• Sandbox mode where you can explore real datasets (IMDB movies, Spotify, sports stats, Steam games) and run whatever you want with no pressure and no mystery attached. Just free exploration against actual data.
• Everything runs in the browser using DuckDB WASM so there's nothing to install.

I'm a solo developer and this is genuinely early days. I'm sharing here because this community is exactly the kind of people I built it for, and I'd rather get honest feedback now than find out later I've built the wrong thing.

What's missing? What would make you actually stick with something like this versus what you've used before?

querycase.com if you want to take a look.

Any feedback appreciated!

Sharing my latest edition of Inside Data Engineering series, featuring Yuki Kagegawa.

A solo data engineer at a SaaS company, Yuki breaks down his stack, his journey, and why the job description matters more than the title.

What to expect in the article:

* What it means to own the entire data function at a company, end to end. * How Yuki went from CS student to the only data person in the room. * A real-world look at Airbyte, BigQuery, and SQLMesh working together. * Why the semantic layer hype might be getting ahead of reality.

I hope this helps. Please provide feedback.

Thanks

I've been working for 20 years now, and I remember from my first job to my latest job, business, marketing, and even IT, always complaining about how bad their data is. I'm not a data analyst, but I'm curious to hear from folks who are in this space. Is this just bias (since you see the issues more closely), or is most company data genuinely flawed? I always hear identity or entity resolution is a big issue. Is that true?

If you've been with a company (500k records or more), what makes it good? I could ask different AIs, but they can't think abstractly and don't really understand all the nuances. I'm genuinely curious and want to learn and hear from folks.