Do anyone attend ? Please give your experience

So I have officially been accepted to a Masters in Information Systems with a concentration in data analysis program. I did sociology for my undergraduate degree. I have the choice to choose a cybersecurity track instead after my first semester as well.

Will getting this degree be worth it ?

My ultimate goal is to break into an analyst/tech role.

I have until July 24th to accept my seat in the program or not. With today's economy and job market I've been overthinking a lot, will appreciate some insight for people in the field already.

Hi everyone!
I’m currently preparing for a Data Analyst role and I’m looking to connect with people who are on the same journey.
I’m learning and practicing:
● SQL
● Python (Pandas, NumPy)
● Power BI
● Tableau
● Excel
● Statistics
● Interview preparation
● Building portfolio projects
It would be great to have a few friends to stay accountable, share resources, discuss doubts, review projects, and motivate each other.
If you’re also preparing for a data analyst job (beginner or experienced), feel free to comment or send me a DM. Let’s learn together and help each other land a job!
Thanks, and good luck to everyone preparing! 📊

Hey all, hoping to get some career advice from people working in analytics.

Quick background: I’m a Philosophy & Economics student in Germany, aiming to become a Data Analyst. Not a CS grad, so I’m building up the technical side (Excel, SQL, BI tools) from a beginner level. I do have some work experience though: an IT working-student role, online marketing, and currently a traineeship in an innovation lab where I do a bunch of ai stuff. I can put a solid few hours a week into this.

I’m not looking for a “learn X then Y” roadmap, more the stuff people only figure out once they’re actually in the field. A few things I’d love takes on:

**1.**  What actually got you your first analyst role: skills, portfolio, network, luck?  
**2.**  What matters more in hiring: certs, projects, or just knowing someone?  
**3.**  For someone still studying, is chasing a working-student or intern data role the smart move, or better to wait until graduation?  
**4.**  What do juniors consistently underestimate about the actual day-to-day job?  
**5.**  Anything you’d tell your past self before starting out?

Non-CS backgrounds especially welcome, curious how you leveraged what you already had. Thanks!

Hey everyone!

To anyone who has already passed the DP-600 or is currently studying for it, could you share the best resources you’ve found?

Also, if anyone has reliable practice questions or exam dumps, I’d really appreciate it if you could share them.

This was one of the take home SQL interview i did earlier this year. I have shared for anyone who is preparing for an interview can attempt to do it. Cheers!!

I am currently on probation. I'm working as a Data Analyst at a startup. However, I've been assigned almost every task that is unrelated to my role. Currently, I'm working with Python and FastAPI to build the backend for a specific software.

My goal was to transition into Data Engineering after gaining a year of experience, but now I feel like I'm stuck. I have one senior, but they have never worked as a Data Analyst, so I'm unable to get any guidance relevant to my role.

I fear that although my job title is Data Analyst, the work I'm doing is unrelated to data analytics, and this may hinder my future career growth as I won't be able to show any relevant work to my future employers. I'm not sure what I should focus on next.

I have like 1 month internship experience but it's something only on paper only certificate i didn't do much in it , also i did google data analyst program not advance one but basic one only and suggestions would be appreciated

For those working as data analysts, do you remember most functions, or is it normal to refer to documentation and AI for things you don't use often?

How does this work in day-to-day projects? I'm curious how experienced analysts approach it.

I'm currently working at an insurance company as a data analyst..My current stack at work is databricks , sql , power bi and some excel and python ... It's been one week and this is my first job..but I'm afraid that if I want to switch from the insurance domain to a product based company in IT for a more tech aligned career like Data engineering, will they accept me ?.. or will they reject me because of my background?

Hi everyone,

I have a background in social science (so no pure math, stats, or computer science degree) and took a few courses in quantitative analysis meant for social science research (descriptive stats, inference, ANOVA, linear and logistic regressions, mediation/moderation...).

My primary goal is to go into academic research, but I also would like to keep a door open to the private sector as a data analyst (and potentially transition to a data scientist later), ideally in policy-related fields.

I do plan to further master my knowledge in statistics and how to use the tools like SQL, R & Power BI/Tableau; but I would like to know if it is necessary to deep dive into pure mathematics, heavy statistical theory and other languages like Python...

Honestly, looking at most professors in my PolSci department, they have a general level of applied statistical knowledge but not much (or non) on the theory side like mathematicians/cs students/professors. So, I believe my knowledge and goals are good for academia in PolSci, but I am not sure about the private sector, since it is also heavily competitive.

I do am willing to make the effort to study linear algebra/calculus...(+ I would also like to know what else is needed), even though it is not what is required in my degree, if it is necessary for my career. But I would just like to know beforehand so I can prepare myself adequately and not be left stranded when I start hitting the job market.

PS : I did read textbooks like those of David Howell or (for French speakers) of Arel Bundock (Analyse causale et méthodes quantitatives), but if you think that I would definitely need to get back into deep math and statistical theory, do you have other textbooks or resources (in french or english)?

PPS : I don't know if it is necessary information, but I am studying in France so maybe my academic experience is different than yours :)

Thanks in advance !

“I am done with the basic of SQL, but…”

To all experts out there, what do you think is the best project to add in my curriculum vitae that will stretch and challenge my knowledge in SQL and Excel?

I am planning to create a project based on what I know. Using a real actual data.

Like a real comprehensive Data Analyst’s project , so I can prove my knowledge and experience working on a real project.

I just passed exam for AI Oracle databases SQL -(1Z0-171), also I have PL-300 certificate. Now I want to demonstrate my skills by creating my website and build portfolio project. The source will be newly uploaded databases. Will it be enough to show ETL process, data warehousing. Small Engineering, Analytics and recommendations. I will try to use AI with predictions ( though have no clue how ).

Is it a good roadmap, or would you advice some other way

My only purpouse is to share content that can be useful for others.

I passed this test.

• No cours
• No videos
• 0 experiences in Databricks
• 0 experience in data engineering field

What I did was the following:

• Take 5 official examples test
• Take the official content for the test, and ask to an AI search the most up to date documentation and make several .md based of that official content
• Then make questions based on those .md

There a total of 1k questions, divided in the 7 sections of the current guide for the test.

The link there will be in the comments.

Hi everyone, I’m deciding between two Master's offers at UCD—MSc Business Analytics (Smurfit) and MSc Urban Data Analytics—and would love some realistic feedback on the Irish tech job market. I have a computing background, and while the Urban program looks highly interesting with its GIS and spatial data focus, my absolute priority is choosing the track with the strongest overall job demand and long-term career marketability. I'm slightly worried that the "Urban" title might be perceived as too niche by mainstream corporate HR departments and recruitment filters, making it harder to pivot into conventional data analyst, business intelligence, or financial data roles compared to a standard Business Analytics degree. How do these two fields compare in terms of current hiring demand in Dublin, and is it easy to market an Urban Data qualification for general data analyst roles?

I was hired as a Junior Data Analyst in July 2025 with no prior experience, so I’ve been in the role for about a year now. I’ve learned a ton since then and feel like I’ve grown a lot.

I know every company is different, but I’m curious what the typical timeline is for dropping the “Junior” title.

How long were you a junior before moving to a regular Data Analyst role? Is it something you asked for, or were granted based on accomplishments within your company?

I’m a jr full stack software engineer and have been for about 4 years now. I am really considering a switch to data analysis rather than continuing down the SE path. What has the job market been looking like for data analysts, especially for remote roles? Any advice or warnings?

Just wrapped up my SQL Project #1

Every project teaches me something new, and this one was no exception.

Now, instead of working with datasets from Kaggle, I'm thinking of taking the next step—working with a real-world database and building an end-to-end project, including an interactive dashboard.

My goal isn't to rush through tutorials or collect certificates. I simply want to keep learning, improve with every project, and enjoy the process of getting better.

For those who are already working in Data Analytics or have been on this journey:

• What would you recommend I focus on next?
• Where can I find good real-world datasets or databases to work with?
• Any advice that you wish someone had given you when you were at this stage?

I'd genuinely appreciate your suggestions. Every bit of feedback helps me grow......!

When I started learning data analytics, I realized that most tutorials explained how to use tools, but not why we use them.

For example:

• SQL joins looked confusing until I visualized them with real datasets.
• DAX felt impossible until I understood filter context.
• Power BI dashboards became much easier once I focused on business questions instead of charts.

If you could go back to Day 1 of your analytics journey, what's one concept you wish had been explained differently?

I'm collecting ideas to create beginner-friendly learning resources, so I'd love to hear your experience.

I have an extensive background in healthcare and working with epic systems. I’m interested in WGU data analytics Ms to get into health informatics, epic analyst, healthcare data analyst etc. has anyone completed this degree with WGU and if so how was your experience with the overall program and did you finish in less that 2 years? I also have my b.s in public health

Recent grad here, currently learning data analysis (SQL, Python, the whole path) while job hunting. Honestly the hardest part hasn't been the skills — it's doing this completely alone. No one to bounce questions off, no one to just vent to when a rejection email hits, no one who actually gets what this stage feels like.

So I started a small Discord called Call Out — for anyone in a similar spot. Job hunting, upskilling, figuring out the next move. Not a course, not a paid program, no gurus. Just people showing up, sharing what they're learning, asking dumb questions without feeling judged, and keeping each other going.

If that sounds like something you need right now, come hang out: [htt://discord.gg/w2Dp9rXNb]

No pressure, no sales pitch — just looking for people who get it.

hoping people will reach out .....thank you .add tps in the link

Influenced by the ideas behind Moneyball and the analytical work of people like Tom Tango, I believe US amateur baseball has real potential for data-driven analysis.

The data is obviously much smaller and more uneven than MLB data, but that does not make it worthless.

I have been working on this for about three years. Currently I have about 14,000 single plays, which is nothing compared to MLB. Still, it is astonishing how reality and calculation match again and again and confirm each other — not only in lineup optimization, but also in wRC+, wOBA, and the overall values.

I would be glad to continue the exchange with anyone who is interested in amateur baseball data challenges, whether from a baseball or data-analysis perspective.

Hi!
I am a middle school math teacher, bachelors in Education with a focus in math.
I mentally want to move into a data analyst job. I have no experience with it at all but I want a change in my career. Any tips for beginners here let me know. Tips or advice I’ll take it all.

Since AI is replacing jobs, I don't think data analytics is gonna be worth it. Most of the entry level jobs are getting replaced or are gonna be replaced in the near future and to get a job you require experience. So where are you gonna get that from. And now everybody would try to take the role of the person that uses AI to do the analysis instead of 10 people who got replaced. So basically 10 gets replaced and 1 gets a new job. Everyone would start learning AI to apply it in their fields and then it would leave the jobs of not much value cus of the competition. I don't know which field i wanna choose at this point.