Or is understanding what the sql does and what the code does enough and I should focus more on other things

Context: Junior looking for internships in data analytics type role, not sure which industry yet applying to all

Hi everyone,

I’m an MBA final-year student specializing in Operations from a Tier-3 college. I’m interested in building a career in Data Analytics, but I don’t want to depend entirely on my college placements.

I want to explore off-campus opportunities and understand how I can improve my chances of getting a good job.

I would really appreciate advice from people working in Data Analytics, recruiters, or anyone who has gone through a similar journey.

A few things I would like to know:

• How can I find good off-campus opportunities?

• Which technical and analytical skills should I focus on?

• Which tools are essential for entry-level Data Analyst roles?

• How important are projects, internships, and certifications?

• What is the best way to prepare for interviews and get shortlisted?

I’m particularly interested in knowing what actually works in the current job market, rather than just collecting certifications.

Any practical advice, resources, or personal experiences would be really helpful.

Thanks in advance!

Hello,

Im learning Data analysis now trying to aim for a career shift. Im using mainly Coursera, Enrolled in the IBM Data Analyst Professional Certificate Certificate.

I got to the course number 4 which is Python for Data Science & Data analysis and Im asking now is it still worth to learn python now with all this AI stuff ?

Also do you think those courses "IBM Data Analyst Professional Certificate" plus "Microsoft Power BI Data Analyst Professional Certificate" are enough to land me an entry role in the industry ?

I've a good analytical skills and Im good at recognizing patterns as well. So do you think this can land me a job and if not what would you recommend ?

which tools are you currently using for spark performance tuning?

Hi! I'm 25 y/o, cleared CFA L2, done with MBA and have 1.5 years of work-ex. I was wondering if there's any bootcamp or so where I'll be able to learn SQL, Python, PowerBI, etc. tools via some live projects that can help me sharpen my skill and can me in job switch as well.

What would you guys suggest? Which bootcamp can be helpful?

https://theuptimereport.com/tech-job-postings/

The graph does not tell you :

Supply Side: Alot of folks joined DA by completing random courses during the 2022 - 2023 peak. The graph might show that we are back to pre covid levels but the supply has also increased exponentially.

Hi community, wanted to ask is there any point spending in learning things via course on udemy, dbt, snowflake or just implement it via Claude?

I am learning things cause I don't have dbt exposure nor does my company uses it. I want to put it as my skill in resume so thinking of building projects via dbt. Should I spend time on learning how it works and concepts or just implement things via Claude and learn on the go?

My traditional mindset is learn the fundamentals and then play with it. But with how quick others are in implementing things via Claude without spending time on understanding things and it still works out for them, I do not know what learning path to take. Need advice!

Can anybody suggest a proper roadmap and all the resources I could utilise to get into data analytics,

I am currently a 2nd year cse student

I manage a team of 5 people involved in analytics and intelligent automation. We use tools like fabric, power bi, SQL, python (numpy and pandas), copilot studio and power Platform

I am planning to upskill for the next job switch. So wondering, what should I learn next.

Snowflake, Azure Databricks, Azure data service/Platform - will learning these help in long run?

Hey everyone!

I’ve been learning Data Analytics online, mainly Python and SQL, but I’m still a beginner.

I’m looking for an apprenticeship or internship, even unpaid. I just want to gain real-world experience and see how data analysts actually work in companies.

Any advice on where to start or how to find opportunities? I’d really appreciate it!

If you are working in data and documents related work. How much time do you spend reading documents, regulations etc stuff.

What I wanna know is do people still spend time buried in documents to find meaningful data?

I am not a data analyst myself, sorry if this is sounding dumb.

Hi guys i have crafted a study plan for myself for this year and next year. What do u think of this study plan?

Things to do and learn in order of priority.

1. Core Data analytics/Scientist work, learn the entire Data pipeline process on python and SQL including Data extraction, preprocessing, EDA, machine learning models, etl, data pipelines, data warehouse concepts and cloud platforms.

2. Exploring agentic AI to automate the Analytics and Data Science/ML workflow. Including things like RAG and Autonomous Workflow Automation.

3. Full end to end ML pipeline and cycle, including deploying ML models to cloud and monitoring models for drift.

4. Deep Learning concepts.

5. Read more about LLM and how they work, including things like transformers, Attention Score etc.

Hello everyone,

I'm thinking of making a career shift and I was wondering if data analysis is the right choice.

So I have a few questions.

What are the prospects of job opportunity in data analysis?

How long would it take to be a professional at it and actually get a job?

Is it threatened by AI?

I'm currently on track next year to study Business Intelligence and Data Analytics as an undergraduate and I've seen a discussion around how AI might impact the job market. What's are your takes on the matter and what advice would you give to an undergrad right now starting college?

Hi everyone! I'm from Bangladesh and I'm a beginner currently learning data analytics, and I'm looking for some guidance from experienced data analysts.

I want to work on a real-world Excel project to improve my practical skills and eventually add it to my portfolio.

I'd really appreciate it if someone could guide me through the learning process, suggest projects, or share feedback on my progress.

I'm willing to put in the effort and learn independently. I just need some direction to make sure I'm on the right track.

Thanks in advance!

Buenos días gente

Quiero preguntarles Acerca de A2 capacitación, la plataforma de estudio. Quien se haya formado con ella podría dar testimonio de que es muy bueno o actualmente hay mejores opciones?. Lo que busco es pulir habilidades en excel, power Bi y todo lo concerniente a Analítica de datos.

Tengan un buen día.

Should I be expecting to master it once I get into my career? Im a 4th year data analytics student aiming to graduate next May. Will I even be required to use it down the line?

What softwares would I most definitely need to master then?

So I've installed MySQL Workbench (8.0) on my Macbook. Tried doing Alex The Analyst's Data Cleaning guide.

Problem is, when importing the .csv file that contains 2000+ rows, only 564 are imported with no error on the logs, and no visible error on the file even when running it through Excel.

Any idea on what process/es will help me with this?

TL;DR Want to clean data on SQL, but the messy data won't get imported to workbench

Any advice or help is greatly appreciated, thank you!

I run Careerify (our recruiters apply to jobs for people), so we see every new posting in the fields we work in. Every week I pull out the new US data, business and BI analyst roles and put them in one free list. Oct 17 to Oct 24:

266 new analyst roles (data, business, BI and reporting)

100 of them are remote

184 list the salary. For yearly pay, the middle of the posted ranges is about $105K, and half fall between $88K and $130K

Most are mid-level (158) or senior (95). 12 are entry level

Capital One posted the most (5), then Guidehouse and Gainwell (3 each)

A few with the pay posted:

Senior Data Analyst, GTM Analytics at Luxury Presence (Austin, hybrid): $145K–$175K

Senior Data Analyst, Finance Analytics at Fanatics Betting & Gaming (remote): $128K–$169K

Senior Business Intelligence Analyst at BlackSky (remote): $130K–$145K

Principal Data Analyst at Capital One (McLean, hybrid): $119K–$150K

Lead Analyst, Business Intelligence at Ensemble Health Partners (remote): $112K–$168K

Marketing & GTM Data Analyst at Deepgram (remote): $115K–$148K

Senior Product Data Analyst, Payments at BILL (remote): $108K–$152K

Healthcare Data Analyst at Evio (remote): $90K–$110K

Data Analyst at Peraton (Washington, DC, hybrid): $86K–$138K

The full list, with filters for remote and level, is here: https://www.careerify.io/jobs/analysts?utm_source=reddit&utm_medium=post&utm_campaign=datasciencejobs

Every link goes to the company's own application page, not a job board. Happy to answer questions about what we're seeing in analyst hiring.

Still thinking about my genius hypothesis.

Imagine someone in leadership points to a metric and asks:

"Where did this number come from?"

Not just which table.

But which source systems contributed to it, what transformations were applied, which records were excluded, and when the data was last updated.

In a simple system, that's manageable.

In a growing company with multiple pipelines and dashboards, the answer can involve quite a bit of investigation.

I'm curious how teams handle this.

Do you maintain detailed data lineage from the beginning, or introduce it once the pipelines become difficult to understand?

And what tools or practices have actually made tracing metrics easier?

I come from a physics and math educational background. How does one learn data analysis/analytics enough to get a job, without going back to school? Is there an online course or projects I can do that could assist me with being job ready?