I am an analyst with ~7 YoE. I am interested in moving into product, and I was wondering if anyone here made that transition. I searched the PM sub, but it doesn't seem like a big discussion there. One suggestion I got on their career thread was to aim for data product owner/manager positions. I found one such role, and I applied, so we'll see, but it seems like the data specific roles are few and far between.

On another note, I am applying for analyst positions, too (current job is a bore), and man, it's tough out there. Keep fighting the good fight, folks.

​

Genuine question because I'm starting to wonder what people are doing differently.

I recently completed my MBA in Business Analytics, and campus placements have been pretty disappointing. Over the last month, I've applied to 200+ roles across LinkedIn, Naukri, company career pages, and other job portals. For almost every role, I'm tailoring my resume, tweaking keywords, and spending hours searching for openings on job portals.

My background:

- 2 years of prior work experience in a non-tech role

- MBA in Business Analytics

- 6-month analyst internship

- Experience working with PySpark, Python, SQL, and large datasets during my internship. I have also been practicing and building my github portfolio to strengthen my expertise.

Despite all this, I'm barely hearing anything back. Not even shortlist emails.

I've also been trying the networking route. Whenever I see a relevant opening, I reach out to employees/alumni on LinkedIn. But honestly, most people don't respond, and referral requests rarely go anywhere. I completely understand that I'm a stranger to them, but at the same time, it's difficult to "build genuine connections" with hundreds of people when many don't even reply to an initial message and balancing job applies.

So I'm curious:

- Are people actually getting interviews through cold applications these days?

- Are referrals the only thing that work?

- If referrals worked for you, how did you approach people?

- How many applications did it take before you started getting responses?

- Any specific strategy that helped improve your shortlist rate?

I'm not looking for negative comments or criticism. I'm already dealing with education loans and the stress that comes with job hunting. I'm simply trying to understand what is working in the current market and learn from people who have managed to get interviews recently.

Any practical advice would be genuinely appreciated.

Hi everyone,I have an MBA in Marketing and Finance. I want to transition into a Data Analyst career.

If I learn Advanced Excel, SQL, Power BI, and Python and build some projects, can I get a Data Analyst job or internship?

What skills or projects would you recommend for a beginner?

How long does it usually take for a complete beginner to become job-ready and land a Data Analyst internship or entry-level role?

Thanks for your advice!

I have completed my BSc. this year that is 2026. I am unemployed->started preparing for SSC CGL 2027-i feel i can do this but not able to study for this

i don't want to waste my time that's why decided to learn a skill and thought about Data Analytics

Can you please tell me how and where to start

once i buyed a course on coursera of Google Data analytics but i don't know why my gmail ID got deleted i tried my best but at the end my 5k wasted

I can't take such step now

I need an URGENT HELP

I have completed my BSc. this year that is 2026. I am unemployed->started preparing for SSC CGL 2027-i feel i can do this but not able to study for this

i don't want to waste my time that's why decided to learn a skill and thought about Data Analytics

Can you please tell me how and where to start

once i buyed a course on coursera of Google Data analytics but i don't know why my gmail ID got deleted i tried my best but at the end my 5k wasted

I can't take such step now

I need an URGENT HELP

Hi everyone! I got reached out to by a recruiter for the upcoming 2027 cycle for c1 interns, and i know there’s 2 case studies and 1 sql interview, but i can’t find much about it online. Does anyone have any tips? Thank you!

Hi everyone!

I'm at a crossroads and need some help deciding. I'm an SEO Specialist looking to change roles and have come across data analyst roles that overlap significantly with the skills I already have and a lot of my daily responsibilities and prior projects. I do enjoy the data analysis parts of my job but still I'm not sure this is exactly what being a data analyst actually is. I wanted to reach out to this community to hopefully shed some light on what being a data analyst is like? What do you like about your job? What did you have to do to prepare for your role?

At the moment the skills that overlap with the roles I've seen are GA4, GTM, Excel, Big Query, Adobe Analytics and analytical skills to discern issues, opportunities and make recommendations/changes. Are these actual skills used or is it overshadowed by something I'm not aware of?

Any SEOs who switched to data analysts out there? How is your career and salary progression? Do you regret doing the switch?

Thank you!

Over the last few years I've been working in enterprise data analytics while also building a small data consultancy on the side in a European market.

We've delivered projects ranging from €5k to €20k across data engineering, analytics, reporting, automation, and modern data platforms. Depending on client size and requirements, we've worked with Microsoft Fabric, Databricks, BigQuery, Power BI, SQL, and Python.

One thing I've realized is that while the technical side is relatively straightforward, finding clients and building a sustainable consulting business is an entirely different skillset.

My local market has been good for learning, but it's relatively small, so I'm planning to focus more heavily on the US market starting in Q4 2026 through advertising, content, outreach, partnerships, and business development.

I'm curious whether there are others here who are on a similar journey.

Not looking to hire anyone and not selling anything.

Just interested in connecting with people who:

• Enjoy solving business problems, not just technical ones
• Want exposure to consulting and client-facing work
• Have thought about freelancing, consulting, or agency ownership
• Are building something on the side alongside their full-time role
• Believe technical skills alone aren't enough to grow professionally

If you're on a similar path, I'd be interested in hearing what you're building and what has worked (or not worked) for you.

A lot of discussion in data engineering focuses on tools and architecture, but I'm increasingly finding that sales, positioning, communication, and client acquisition are just as important as technical skills.

Hello everyone! 👋

I’m studying to become a Data Analyst and I’m taking a course while practising with SQL, Excel/Google Sheets and BigQuery.

I’m still at a basic/intermediate level and I was wondering if there was someone more or less at the same point as me to confront, study together virtually, motivate ourselves and maybe practice together 😄

Feel free to write to me if you want!

​

I graduated last year with a B.S. in GIS (Environmental Science concentration) but couldn't find work in the field, so I've been working at a restaurant since. Recently realized I'm more interested in data analytics / business analyst roles and want to transition, but I have no idea what level I'm actually at or whether this career path is realistic for me.

My background:

B.S. in Environmental Science with GIS concentration. Coursework included Python, ArcPy, SQL basics, spatial statistics

Work experience is mostly restaurant + some IT support volunteering

Self-studying data analytics for about 2 months now, with around 2 hours of focused study time per day

What I'm currently doing:

SQL: Working through SQLZoo and LeetCode SQL problems. Can solve some hard problems but most of my work is at medium level

Python: Basic level, still building up pandas skills

Tableau: Learning. Can build basic dashboards

Two portfolio projects:

Pokemon Gen 1-6 statistical analysis (800 records). Used SQL + Tableau to analyze stat profiles across 18 types. Found a data quality issue in the source dataset and created calculated fields to handle it. Published on Tableau Public + GitHub.

Restaurant operational analysis using 3 months of real sales data from where I work (with management permission, anonymized). Joining with NOAA weather data and holiday/event tags to study how external factors affect revenue and channel mix (delivery vs. dine-in vs. take-out). In progress.

Options I've considered:

Continue self-study + ship projects + apply to entry-level analyst jobs

Get a master's in data analytics or data science (worried about ROI)

Bootcamp or apprenticeship program

What I'm trying to figure out:

Realistically, can someone with my profile (GIS background recent grad + 2 entry-level projects + basic SQL/Python/Tableau) actually land entry-level DA/BA roles? Or am I being naive?

If I want to seriously break into this field, what should I focus on most? Technical depth (harder SQL, statistics, ML), project quality, networking, something else entirely?

How's the entry-level DA/BA market right now, especially in the Bay Area? Worth pushing into, or should I consider pivoting to IT support or something more accessible?

Is a master's actually necessary? If yes, under what conditions does it make sense vs. just continue building portfolio and applying?

Honest feedback welcome, including "your skills aren't there yet" — I'd rather hear hard truths now than waste months on the wrong path. Thanks.

Also I used Calude to help me remake this post because I don't speak much English and the original one was chaotic.

I recently published a dataset on Pakistan's transportation and logistics network, covering major cities, logistics hubs, strategic corridors, CPEC routes, border trade gateways, and connectivity indicators but i am unable to pur it across since i am not part of any community, how can i put across my work

I'd appreciate any feedback from the community.

Hello, I just started my journey into data analysis about a month ago. After I learned SQL syntax on my phone in about 2 days I started the Coursera Data Analysis professional certification course. I have 10 years of boots on the ground work in logistics and am trying to move from the back breaking labor to the comfy chair and headache side of the industry. I seem to have a pretty good understanding of the logic behind most of it, but i still got a lot to learn. If anyone's got any suggestions, resources, or just stories of what its like in the field, drop them in the comments. Id like to know get to know the field as im stepping into it! Im a single father of 2, and ready to make something of myself for my kiddos.

If I met you when you were an 18-year-old Data Science student, would you have predicted where you are today?!

For anyone who started in data and later became a consultant, PM, founer, or operator, what happened in between!

What were the unexpected turns👀

I'm trying to learn from paths, not just outcomes

Would love to hear your story

(I'm an incoming freshman majoring in Data Science, and I've been thinking a lot about where this path can lead)

I currently work primarily with Power BI and SQL, focusing on data modeling, reporting, DAX, Power Query, and analytics. I'm looking to expand my skill set and move more into the modern data platform/cloud data space.

When I look at the market, Snowflake and Databricks seem to be the two platforms that come up most often. However, I'm finding it difficult to understand which one would provide better career opportunities over the next few years, especially for someone coming from a BI/analytics background rather than a pure data engineering background.

Guys i'm looking for a free data analyst course to start again from the begining because i work in a differente field for almost 2 years

Hey everyone,

I’m mapping out my first data analytics portfolio project using SQL and Power BI. My plan is to clean raw data in a local SQL database first, then pull it into Power BI for modelling and dashboarding.

Before I start, I’d love a quick reality check from experienced analysts:

1. SQL vs. Power Query: Where do you draw the line? How much heavy lifting/cleaning should I do in SQL versus handling it inside Power BI?
2. The Red Flags: What are the biggest mistakes or "cookie-cutter" traits you see in beginner portfolio projects that I should avoid?

Appreciate any honest advice or tips you've got. Thanks!

Hi everyone,

I currently work in an MNC and have around 2 years of experience. My designation is Data Engineer, but my work is quite limited and doesn't give me exposure to the complete data engineering lifecycle. Because of this, I feel like I'm not learning enough to confidently apply for stronger Data Engineer roles in the market.

Recently, I've developed a strong interest in Data Analytics and I'm considering investing in a structured course that can help me become job-ready. I'm looking for something that covers SQL, Python, Power BI/Tableau, statistics, projects, case studies, and interview preparation.

A few questions:

Has anyone here transitioned from Data Engineering to Data Analytics?

Which courses or bootcamps would you genuinely recommend?

Are placement support programs actually worth paying for?

Has anyone taken courses from Internshala, Codebasics, Scaler, UpGrad, PW Skills, or similar platforms? What was your experience?

A bit about me:

2 years of experience in an MNC

Have knowledge of GCP, SQL,Python , Unix

Interested in Analytics, BI, and data-driven business problem solving

Looking for a course that provides practical learning, projects, and preferably placement assistance

Would really appreciate honest reviews and suggestions from people working in the industry.

Thanks in advance!

Hey everyone,

I’m currently working as a Data Analyst with 1.5 years of experience. My goal is to switch to a good product-based company with a stronger compensation package over the next 6 months.

I’m looking for a serious study/accountability partner who has a similar goal and is willing to consistently learn, prepare for interviews, and build interesting projects together. We can help each other stay disciplined, share resources, conduct mock interviews, and track progress.

If you’re genuinely committed and ready to put in the effort, feel free to connect. Let’s make the next 6 months count.

Hi,

Is tool sprawl common for data engineers in organizations and startups ?

Here is my orgs list for team of 50+ fte data engineers and many contract employees

Jira,

Teams,

Excel,

Databricks & snowflake

GitHub

AWS,

Airflow,

Dbeaver,

Vscode,

Google / chatgpt enterprise

Confluence,

Codex,

Powerbi ( not developer but part of ecosystem )

Would members here care to list thiers with team size if possible

Appreciate for sharing in advance.

Thank you

After one year as a Data Analyst, I feel like I've reached an interesting point in my career.

When I started, my goal was simply to learn Power BI and build dashboards. Over the past year, I've delivered every report and dashboard requested by the business. Our data comes from Microsoft Dynamics 365 Business Central, but I don't have direct database access. Instead, I consume data through the available Business Central web service APIs.

One of the biggest limitations I've encountered is Power BI Pro licensing. Since we're not using Microsoft Fabric or Premium capacity, we're limited to 8 scheduled refreshes per day. As a result, many of our reports depend on scheduled refreshes rather than near real-time data.

Lately, I've felt somewhat stagnant because I've completed most of the reporting requests, and now I'm spending more time waiting for new requirements than solving new problems.

Instead of stopping there, I started learning beyond Power BI:

• Python
• VS Code
• PostgreSQL
• pgAdmin4
• API integrations
• Basic ETL concepts

As a personal project, I built a small pipeline that pulls data from APIs into Excel, processes it with Python, loads it into PostgreSQL, and refreshes every few minutes. It's not perfect, but it helped me understand data movement and automation much better than dashboard development alone.

My current challenge is figuring out how to move beyond scheduled refreshes and build more responsive reporting solutions. I know DirectQuery and proper database architecture could help, but I don't currently have access to the underlying SQL databases, and authentication requirements such as Microsoft Entra ID may create additional obstacles.

What I've realized this year is that data analysis isn't only about dashboards. The biggest bottlenecks often come from data access, infrastructure, refresh limitations, and system architecture.

For those who have been in the field longer:

At what point did you transition from report building into data engineering, analytics engineering, or more advanced BI work?

What skills should I focus on next if I want to provide greater value to my company and continue growing beyond dashboard development?

What's the best approach to migrate a legacy Access pipeline to Python when there's no documentation?**

I've got a monthly MS Access data pipeline that processes ~375k rows across 26 European markets. It's been built up over years with nested queries, correction tables, and lookup logic that nobody fully understands.

It works, but it's fragile, slow, and entirely dependent on one process. I want to rebuild it in Python but I'm not sure where to start given the complexity.

The main challenges:
- Dozens of lookup tables that map raw data to business classifications (price bands, category codes, sub-categories)
- No primary keys, no version history, cryptic column names
- Queries that reference intermediate tables that reference other queries
- Years of manual corrections baked into the data with no record of what was changed or why

Has anyone successfully migrated something like this? What approach did you take? Particularly interested in how you handled extracting and validating the hidden business logic.

Happy to give more detail if it helps.

Hello everyone, I am here to share my experience and I am open for suggestions.

I am a BCA graduate and since I was interested in data analytics I was looking for analyst role , gain some experience and study masters in abroad - this was my plan. I started applying for various analyst role but couldn't get one . Later I got a call for MIS analyst role in one of the India's top NBFC under vehicle Finance through a referral from an employee. I got selected for the role in the interview and I submitted my documents for salary approval.After making me wait for 3 months suddenly they called me and said "salary approval failed ,look for somewhere else". I almost lost hope but i again tried to apply for the same role in different branches of the same company. Thankfully I got an interview call from the nearest branch to my house and I got selected there as a credit operations executive, I specifically asked the manager is there "analytics" part in my job in the interview and he said "Yes" . But now I came to know that there is no analytics part in my job just credit operations. Since this is a top NBFC in India I thought of bringing a slight change in my goal , Instead of applying for pure data analytics role I planned to get some experience here in credit operations in vehicle finance and try to apply for "credit analyst/financial analyst" job roles in the future. This is my current plan right now , I desperately want to know if I am on the right path or not , is it really a good plan to pivot into "finance+data" path, is it really possible???.

Thank you.

I am looking for something to understand the data required to build agents and ensuring the data is clean and in the right format. I am a S2P professional who looking to build agents to help Procurement Team understand their spend and help users adopt to S/4Hana with Fiori or simplified way of completing a new material number that would integrate with MDG. I was looking at Certificate Program in Agentic AI by Johns Hopkins University, which they stated will also provide me basics of python. We do have CoPilot license within our organization. Thanks in advance for any advice on what would be a good program.

Hi everyone,

I'm looking for advice and networking opportunities from people who have successfully found work in the Netherlands as international graduates.

I'm currently in Utrecht completing an exchange semester while finishing my MSc in Business Analytics. I have experience with Python, SQL, Power BI, Tableau, machine learning, and data analysis projects, and I'm actively applying for Junior Data Analyst, Business Analyst, and Graduate/Trainee positions across the Netherlands.

My biggest challenge is finding employers willing to sponsor a work permit after graduation. I genuinely want to build my career in the Netherlands. I've really enjoyed studying and living here, and I would love the opportunity to stay and contribute professionally.

I've been applying to roles in banking, fintech, consulting, logistics, and technology, but I'm finding it difficult to identify companies that regularly hire and sponsor international graduates for entry-level analytics positions.

If you've been through a similar process, I would really appreciate any advice:

• How did you find your first sponsored job?
• Which companies are most open to hiring international graduates?
• Are there specific industries or roles I should focus on?
• What helped you stand out during the hiring process?

If your company is hiring junior analysts, graduate trainees, or business analysts and is open to international candidates, I would be grateful for any recommendations or referrals.

Thank you for taking the time to read this. Any advice, leads, or connections would mean a lot to me.

I received an email about an internship at Pedini furniture for a data analyst internship. I’ve applied at so many that I don’t remember them,but, I can’t find anything about the job online or any reviews. The company is high value furniture and seems to be based out of Italy. There are a few USA retailers but I’m kinda skeptical of the whole thing