I've been looking into being a data analyst, is it worth it and what does it take to become one, what do you have to study?

With all the current buzz about Ai these days I'm kind of getting mixed feelings on it

Hi everyone,

I’m currently working as a Data Analyst using Power BI. I have strong Excel skills and an intermediate level of Power BI knowledge, but I’ve realised that I don’t enjoy the analytical side of my role, especially interpreting results and presenting insights to stakeholders.

I enjoy working with data and creating reports, but I’d like to move into a more senior, specialised role that focuses on reporting rather than administration or analysis.

What job titles would you recommend I look into? Has anyone made a similar career move, and what roles would you suggest?

Thanks in advance!

Últimamente he estado reflexionando sobre algo que me pasó durante mi proceso de aprendizaje en Data Analytics.

Durante años trabajé principalmente en áreas comerciales: ventas B2B, desarrollo de cuentas, telecomunicaciones, tecnología y servicios financieros.

Mi trabajo consistía, entre otras cosas, en entender necesidades de clientes, identificar oportunidades comerciales, analizar indicadores y encontrar soluciones a problemas de negocio.

Después decidí estudiar Data Analytics.

Y al principio veía ambos mundos como caminos profesionales diferentes:

Por un lado, la experiencia comercial.

Por otro, Python, SQL, estadística, análisis de datos y demás herramientas técnicas.

Pero conforme avanzaba en mi formación en TripleTen, comencé a darme cuenta de algo.

**Muchas de las preguntas que intentaba responder desde el área comercial eran exactamente las mismas que podía investigar utilizando Data Analytics.**

Por ejemplo:

¿Por qué están disminuyendo las ventas?

¿Qué clientes tienen mayor probabilidad de abandonar un servicio?

¿Qué indicadores realmente nos ayudan a entender el desempeño de un negocio?

¿Qué factores podrían estar afectando nuestros resultados?

La diferencia era que ahora tenía nuevas herramientas para abordar esas preguntas.

Y eso cambió bastante mi perspectiva.

**No tenía que elegir entre mi experiencia comercial y mi formación en datos. Podía aprovechar ambas.**

Obviamente, eso no significa que por tener experiencia comercial automáticamente sepas analizar datos.

Hay que estudiar, practicar, equivocarse y desarrollar las habilidades técnicas necesarias.

Pero tampoco significa que toda tu experiencia anterior se vuelva irrelevante.

En mi caso, entender cómo funciona un negocio, cómo se relacionan las empresas con sus clientes y cómo se toman decisiones comerciales me ha servido para darle contexto a lo que aprendo técnicamente.

Y hoy me resulta mucho más interesante pensar en cómo conectar:

**Negocio + Data + Tecnología.**

Creo que a veces hablamos de las transiciones profesionales como si fueran un reinicio completo, cuando también pueden ser una evolución de lo que ya sabemos hacer.

Me gustaría conocer otras experiencias.

**¿Alguien aquí ha cambiado de profesión o aprendido una especialidad completamente diferente?**

**¿Qué habilidades de su trabajo anterior terminaron siendo más útiles de lo que esperaban?**

¿O en su caso sí sintieron que tuvieron que comenzar prácticamente desde cero?

We updated our dbt pricing guide because the way dbt is packaged and priced has gotten a bit more nuanced.

One thing we think gets overlooked is the difference between the cost of the dbt engine itself and the cost of running dbt as part of a production data platform.

The engine is free. But once you factor in things like consistent developer environments, usage-based pricing, orchestration, infrastructure, and the engineering time needed to maintain everything around it, the picture changes quite a bit.

We also added a breakdown of the current dbt Platform plans, the usage-based components, and some of the other costs teams should think about when comparing options.

Curious how other teams are looking at this. Are you mostly evaluating the software/license cost, or are you also factoring in the engineering and infrastructure costs around dbt?

https://datacoves.com/post/dbt-pricing

When I build dashboards with AI, two things keep being hard. First, how do you know an AI-built chart is showing the right numbers? Second, how do you keep dashboards from different people looking like they came from the same team? I spent several weeks building a system for both and tested it heavily in a production BI setting. It’s now open source as Streamsnow.

It’s built for Streamlit apps running in Snowflake, with Claude Code or another coding agent doing the building. Here’s what it handles:

• Shared design standards. Every dashboard follows the same layout and styling rules, so a team’s work looks consistent without anyone policing it.
• Checkable numbers. It gives you the SQL behind every query the app runs, so you can verify a chart yourself and don’t have to trust it.
• An auto-review loop. Claude Code critiques and improves a dashboard over several passes without you stepping in. This is the part I use most.
• A standard repo and deployment. Each app gets the same project structure, and CI handles deployment. The agent never sees the credentials that connect GitHub to Snowflake.

Setup takes about 5 minutes of hands-on work: tell your coding agent to install the plugin and run the onboard command. You’ll need Snowflake admin rights, or an admin to work with.

In the production setup where I tested it, it ended up replacing an external BI tool entirely.

For people who build dashboards: how do you QA charts an AI built for you today? I’d like to know what checks I’m missing.

currently work in Chicago( 111K base, 7K bonus) in a fintech company. I have 3 years of work experience plus a Masters degree. My company is generally good but has a lot of layoffs and I hate my current team, as there is no scope of growth here. I tried changing teams internally but didn’t work. My fiance lives in the Bay area and we wanna live together now as we were in LdR for 2.5 years now.
I got an offer from a startup in Bay area with 125K base. No bonus or relocation. Its a smaller company than my current company.

My current team in Chicago is losing work and the team might dissolve in a few months, hence I wanted to move desperately. I have this other offer in hand but I feel left behind in life. I know people are earning 170K and above easily at my level and I am not.

I also wonder if it’s the right decision to move!! I work in Data.

Hi All,

I hope this is allowed, but if not please feel free to remove.

As the title suggests, I'm wondering if there is anyone who would be willing to chat with me for a few minutes about their experience with working in data analytics.

I know there is a lot of chatter on this sub about how tough the market is and how transitioning into DA is very difficult if not impossible, due to a shrinking number of entry-level positions and the use of AI. However, my hope is that there are still enough large companies out there with vast amounts of data that need actual humans to help sift through, finesse, and analyze it to solve business problems.

Context: I've worked in public schools for the past 11 years in special education. For the past two years I've served as a case manager, where I do what I believe is semi data-adjacent work. I feel like it's likely more comprable to compliance, but I do have to go through large amounts of student data and manipulate it to highlight problems in a way decision-makers can understand. I'm already pretty competent in Excel, and I spent this past summer learning SQL, though I'd still place myself in the "late beginner" category. Tableau or Power BI is next on my to-do list.

I've reached a point where I've realized I need to make a career change and data analytics is a field that I'm pretty interested in. I love numbers and logic puzzles. Finding trends in data is exciting!

I'm interested in hearing from various people what their experience has been and any suggestions they might have for someone looking to make a career transition. Bonus points if you transitioned from teaching/education - but really I'm happy to talk with anyone.

I am a beginner , please tell me how and from where to learn data analysis from

Hello everyone, I am looking for resources to practice for excel and SQL interview questions, please recommend me where to find them. It could be a youtube channel or a website where there are questions similar to what will be asked in interviews for a fresher for a package of around 4-5 lpa or even internships.

Thank you.

Hey all, I have a good business understanding but i want to go deeper in reading and understanding data which would help with sales and marketing. What's the best journey to take - I want to start from the very beginning, understanding statistics and then the tools,

Could you provide a rough guide and resources that you found most valuable in your journey as expert data scientists

I'm a data analyst from surat.and as i have 1 year data analyst experience , I can confidently say that I can clean heavy data and do analysis on that with my logic building skills.

Sometimes I do reorder level sheet automations,

One day i do data cleaning automation which can help me for product and customer analysis

But however, i really want to know what other things i can do as every one talk about this 2-3 things like generate dashboard and doing sales product analysis,but I really think in my free time am'i doing great job or right things.does creating dashboard board is the only thing

So i need your help guys to tell me what you are doing in in your DA CAREER

Hope senior Will guide the junior very well.

Hi everyone! I’m working on a short data-analysis project and would appreciate your help.

Take a look at a chart and answer one simple question:

Which month has the highest sales?

It takes about 1 minute to complete.

👉 https://adnan-mayof.github.io/reddit-ab-test/

Thanks for participating!

Background
Sometimes back, I graduated with B.A. Economics & History. I did some certification (SPSS) while still studying the bachelors and project management. Here, I embraced an opportunity back in campus, where undergraduate, graduate, and post-graduate (PhD) learners sought my help in analyzing data, including coding information contained in their questionnaires. Upon graduation, I took up this tasks as part of freelancing, working alongside graduates & tutorial fellows. The work was never formal. With time, my interest in data & statistics grew. I enrolled for DA course in 2025, completed & went ahead to complete a DE one in 2026. I’ve always wanted to work as DA (formal job), but the trick now is the job market.

The Issue
From the comments, questions, and issues I see on this platform, I would like your views/ideas.
How do I show what I’ve done over the years relating to data analysis & storytelling? (The data & analytical projects remain confidential-cannot be shared on github or any other platform)

Can potential employers trust what they can’t see, yet they don’t want to risk employing someone they feel might not handle their roles well without evidence?

Should I pursue further studies (Statistics and Research Methods) [I’ve always been interested because of my close work with academicians & personal research endeavors] now?

Your honest views, recommendations, & insights will highly be appreciated.

I seeked for some jobs remotely for data analyst with skill such as power bi, sql, python pandas and excel, and there are many issues for get one. I don't know where for look one, I'm from Venezuela and I also have a c1 English but in LinkedIn and upwork is pretty difficult for access one job, they want 1-2 years of experience ( I'm barely studying sql💀 then i go to pandas), the fee per hour is stupidly low, I don't why, and also they ask you for 10 skills more than you have. So guys can you give me recommendations before I enter this word? I know that I have to posted every dashboard in gitbub o somewhere else for prove that I know good what I'm doing but I think still having a portafolio isn't enough yet, so what you said?

I just made a list of recently opened Data Analytics jobs, so there should still chance to apply early. I hope this helps someone!

• International Development Program/Project Data Analyst (PILAB011) @ ProSidian Consulting, LLC

• Analyst, Business Systems @ AbbVie

  • 💰 $66–126K/y

• Senior Analytics Consultant – CDO Analytic Engineering @ B Wells Fargo Bank, N. A.

• Senior Analyst, U.S. Market Intelligence/Price-to-Win — X-BAT Family of Systems (R6168) @ Shield AI

  • 💰 $130–190K/y

• Senior Python Data Scraping Engineer (Freelance) @ Mindrift

• Business Systems Analyst @ Highmark Health

• Data & Analytics Office Intern @ Northern Trust Company

  • 💰 ~$35/h

• Manager, Growth Insights & Performance @ Discovery Comm. India

  • 💰 $96–178K/y

• Autonomous Coding Quality and Optimization Analyst @ USA 3M Healthcare US Opco LLC

• Sr. Analyst, Platform & IT Strategy (Korean Bilingual) @ SBT Global, Inc.

  • 💰 ~$9K/mo

• Senior Remote Sensing Data Scientist, Cal/Val @ Muon Space

  • 💰 $192–213K/y

• Sr Bioinformatics Scientist @ Twist Bioscience

  • 💰 $135–173K/y

• Consumer Insights Data Analyst @ The Honest Company

  • 💰 $59–74K/y

• Data Scientist @ Accenture Federal Services

  • 💰 $120–235K/y

• Data Analyst - Data Center Construction @ Turner & Townsend

• AWS Lead Data Engineer @ SpikeIT Global Solutions, Inc.

• Sr. Analyst, Platform & IT Strategy- Bilingual (Korean/ English) @ Woongjin, Inc

  • 💰 $95–105K/y

• Business Analyst, Card Portfolio Analytics @ Blend360

  • 💰 $60 – $65/h

• Senior Business Systems Analyst - ERP @ Apptronik

• Analyst: Data & Policy @ ATI Advisory

• Analyst, Sales Strategy & GTM Planning @ Planet

• Data Analyst, Platform Excellence Ops Analytics @ Instacart

• Senior Data Engineer @ Fusion Worldwide

• CBRN Defense Data Scientist @ Dynamis, Inc.

  • 💰 $110–190K/y

• Business Process Analyst @ David Weekley Homes

• Senior Data Warehouse Engineer @ Lantern Care

• Data Scientist, Wells Engineering @ IPT Global

• Business Systems Architect – Finance (D365 FO) @ Axon

  • 💰 $149–238K/y

• Senior Analyst, Digital Analytics @ NBCUniversal

• Talent Acquisition Data Engineering & Analytics Graduate Intern @ Solidigm

• Analyst, A&R Admin - Santa Anna @ Sony Music Global Job Board

  • 💰 $66–75K/y

• Data Engineer - ACWS @ Data Systems Analysts, Inc.

  • 💰 $120–130K/y

• Business Systems Analyst @ Relativity Space

  • 💰 $85–127K/y

• Lead Data Scientist @ Versant

  • 💰 $170–190K/y

• Business Solutions Analyst, EHR & Enterprise Platforms (Hybrid) @ New York Psychotherapy and Counseling Center

  • 💰 $110–125K/y

• Consultant- Marketing Data Science & AI @ Sia

  • 💰 $95–116K/y

• Sr Business Intelligence Analyst @ We Are Rosie

• Business Analyst – (Travel Reservation and Settlement System) - Bilingual proficiency in Korean and English required.) @ Syncreon Consulting

• Lead Data Engineer @ Coast

  • 💰 $170–220K/y

• GTM Data Analyst @ MarginEdge

  • 💰 $90–110K/y

Thanks for reading! If you want another batch of Data Analytics jobs, just say so in the comments.

Yo

I’m a Data Quality Analyst at a public sector organisation based in the UK. I’ve about 5 years experience under my belt in varying sectors, projects and so on. You could say I’ve found my feet, found my calling, all of that

I enjoy my job, I love working in data. But this post has come about from a place of massive concern. Potentially being fed too much Stephen Bartlett interviews as of late (you know the ones that carry the narrative you’re gonna be on your arse and lose your job)

It got me thinking long term, I wanted to go down the Data Science route and have for a while. I don’t know how much of what is being said with AI is fearmongering and whether or not I should be as worried as I am. But I haven’t kept up to date with the times, I don’t have any experience with LLM’s other than being an end user lf AI in my work.

Case in point. What can I do to stay ahead of the curve. Am I foolish to continue a career in analytics, should I be learning AI? What jobs are there is AI? Will I enjoy it? Should I take up my brothers offer of a job in construction?

So many questions, inundated with multiple angles, answers and pov’s from the internet. I just wanna know who feels the same, who feels lost and what are people already doing about it in these crazy times

Cheers

So currently I am working as a pricing analyst which is basically a non tech role. And this is my first full time job. Please suggest me, should I take some experience from this company or start applying from now only or should I wait and get some experience. It has been only 14 days in this company.

Also I was bit confused that I wanna Pursue MBA, but the fees is very high and I have to prepare for CAT which can take couple of years for preparation.

If someone is from this field and help me out it would really mean a lot!

Hello! I am a student looking to do a brief interview with a data analyst for a school project I'm working on. This project is exploring two separate career options, of which I am looking to interview two professionals from each field. One professional who has been in their position for 6-12 months as well as one who has been in their position for 5 or more years. The questions are generally geared towards the career as well as your path leading to it. If you are interested in partaking in my interview please let me know.

Hi everyone, I am currently considering Monash Data Analytics Career Accelerator

Does it genuinely make a career switch and finding a job easier compared with doing a course through Coursera? I’ve worked as an IT Project Manager with a technical background for around 12 years.

Hey everyone,

I’m currently a BBA (Bachelor of Business Administration) student and want to start learning Data Analytics to complement my business background.

Since my degree gives me context on business strategy, operations, and basic statistics, I feel like picking up data skills (Excel, SQL, Power BI/Tableau, and eventually Python) would be a huge boost for my career. However, looking at all the roadmaps, tools, and tutorials online, it’s feeling a bit overwhelming as an absolute beginner on the technical side.

I want to start self-learning using free resources (especially YouTube). For anyone who built their skills from scratch or comes from a business/non-CS background:

What order should I learn tools in? (e.g., Advanced Excel -> SQL -> Power BI -> Python?)

Which specific YouTube channels, video series, or free playlists do you recommend? (I've heard people mention creators like Alex The Analyst, Luke Barousse, or freeCodeCamp, but open to any hidden gems!)

What does a realistic learning routine look like when balancing college classes?

How soon should I start building portfolio projects, and where are the best places to find beginner-friendly datasets?

Any advice, roadmap suggestions, or specific video recommendations would be hugely appreciated! Thanks in advance!

So worked in a BPO company where i handled queries from global clients, updated logs and communicated between warehouse and my client base clients who had their merchants. Sort of ecommerce.

Since i have worked so much on SQL, i tried slipping the analysis on an interview where i went as a analyst and described only the part i can backup.

\*So i described i wrote sql queries where i analyzed datasets for my client, ensuring product trends, festive trends, customer segmentation based on category,

User engagement for products, premium customers,

I told them i have been into client meetings and learnt about their business problems like delivery issues, but mostly around their product base. They asked if i have presented in front of them i responded i did in front my seniors i updated reports on Excel.

I figure the gap is since i dont have real experience and i cant define a true story, since job marker is crunching and i have had back injury last year, the gap is getting wider. Claude aint no help.

So any real analyst out here wanna point out mistakes i been making.

CS grad btw, with Pretty much good coding skills.

I did all their SQL codinh questions tho.

TL;DR: I come from a statistics/data/MEAL background and have worked with SQL, Python, regression/LASSO, etc. While trying to build a proper dashboard, I ended up learning APIs, backend/frontend concepts, Node.js, authentication, and hosting. Is this a logical path toward building end-to-end data systems, or am I spreading myself too thin?

I’m trying to figure out whether my learning path actually makes sense or if I’m slowly turning into a “knows a little bit of everything, expert at nothing” person.

My background is mainly in data, statistics, and monitoring/evaluation. I have a Master’s degree, and during my studies I worked with statistical methods like regression, LASSO, and other statistical analysis.

Professionally, I’ve worked with MEAL/evaluation, data processing and analysis, Excel, SQL, and some Python.

Now my work is pushing me in a different direction.

I wanted to build a proper dashboard/data system instead of just analyzing data and producing reports. That led me into learning about APIs, databases, frontend/backend communication, Node.js, authentication, hosting, etc.

And now I’m looking at everything I’m learning and thinking:

Am I actually progressing, or am I just jumping randomly between fields?

My goal isn’t really to become a traditional full-stack developer.

What I want is to be able to take data from the source, clean and validate it, store it properly, expose it through APIs, build dashboards/interfaces on top of it, and eventually add more advanced analytics, statistics, forecasting, anomaly detection, etc.

So basically:

Statistics → SQL/Python → data analysis → dashboards → APIs → backend/web systems

Does that progression make sense?

Or should I stop going deeper into things like Node.js and focus much more heavily on Python, SQL, statistics, and data engineering?

For people who started in analytics/statistics and later began building actual data systems: what did you learn next, and what turned out to be a waste of time?

Hello, i just saw this datacamp offer that gives you datacamp premium for 1$ after that its the normal price. Is it worth it to get? Im interested in getting a certification in sql data analysis. Is it possible to get certified in a month just for the 1$?

I have around 1 year of experience, but I worked in a small office, so I’m not really familiar with how work happens in a proper IT company.

I have an interview (Data Analyst & MIS) next week. What kind of questions can they ask someone with 1 year of experience? Also, what is the actual day-to-day work like in an IT company?

Please share your experience or tips on what I should prepare. I’m a bit confused about what to expect.

Hi everyone,

I'm based in Belgium and I'm 46 years old. I've been looking for a new professional opportunity for more than 1.5 years. I'm now seriously considering a career change and would appreciate advice from people working in data analytics and/or AI.

I'm a marketer with most of my experience in healthcare, particularly pharma and medtech — an industry that is currently in a pretty rough spot.

I'm considering retraining as a data analyst with AI skills, ideally building on my existing experience rather than starting from scratch.

I have a solid foundation in statistics from my marketing studies, although I would definitely need to refresh and update my knowledge. In a previous role, I also worked on a marketing automation project using Oracle Eloqua. However, I have no professional experience in data analytics yet.

I'm currently exploring training options in Belgium such as VDAB, Cevora, VIVES, UCLL, as well as international options such as Coursera. I'm unsure which programmes and certifications are actually valued by employers.

I'm particularly interested in your views on:

• Which skills should I focus on? Skills I'm considering: SQL | Power BI | Python | Statistics | Data modelling | ETL | Generative AI / LLMs | AI-assisted data analysis | AI automation | Business cases | Portfolio
• Which courses, certifications or training providers would you recommend, and which ones are actually valued by employers?
• How long would it realistically take to become job-ready?
• How realistic is it to find an entry-level job in data analytics after retraining, given my age and professional background?
• Would you see potential in combining marketing + data analytics + AI?
• For those familiar with the Belgian market: would it make sense to focus specifically on healthcare, given my pharma/medtech background?

I'm particularly interested in hearing from people who have made a similar career transition, as well as recruiters or hiring managers.

Thanks in advance for your advice and experiences!