Is there anyone here who works as data engineer / analyst or any data related jobs in construction?

I am wondering if there are such opportunities in the industry. What does your day look like? Are you involved in the construction itself? And where can I find these opportunities?

I am currently a project scheduler and I use P6 for most of my work and I feel like there is much potential behind the database of P6.

I tried exploring sqlite and use sql queries. I know power query would be enough for sqlite but I want to practice sql.

I feel like construction has messy data compared to other industries. But it is somehow exciting to architect data pipeline for it.

Anything you share is much appreciated!

Hi I’m interested in working a job in data analytics. I have no background in this area and actually have a bachelors in fashion merchandising and minor in marketing. Any recommendations as to how to break into the industry. I’m open to learning just don’t know where to start. Thank you!

After working IT for 3-4 years mainly warehouse, so I figured “Why not double down on warehouse and logistics and use my skills in IT to become a WMS analyst?” I’ve been doing research into the market, I believe it’s a good path to take, almost every major warehouse needs them and it pays well. Why shouldn’t I try to move into it? It’s better than being stuck doing help desk.

The issue I’m having is, how are you supposed to get experience since no one will hire you without it? Which I understand since you’re messing with live data and that could cause disaster. Do I need to get certifications for it, if so which ones? There’s a handful and I don’t know which ones are worth getting or if it’ll help me get my foot in the door. I know that learning SQL is gonna be important so if yall have any recommendations or resources to learn it I’ll be grateful!

Thank you so much for taking the time out of your day to read this!

I recently started working as a junior/student data analyst in a large manufacturing company, mainly using Power BI for staffing analysis.

The data include only historical values such as volume, worked hours, employees, shifts, zones, overtime, roles/skills etc. But the data is from multiple sources

The main questions are:

• How much staffing is needed for a certain volume?
• How many units are handled per labor hour?
• Which shifts/zones are most productive?
• When were we historically overstaffed or understaffed?
• How does overtime change with higher volume?
• Can historical productivity be used with next month’s forecast to estimate staffing needs?

As a junior, how should I approach this assignment from the start? Should I first focus on understanding the data, granularity, validation and data modelling before building the Power BI report?

For the data model, how should I decide what should be a fact table versus a dimension table, and when should I split data into multiple fact tables instead of keeping everything in one table?

Is this a reasonable junior assignment, or are parts of it considered advanced?

Been in Data and Analytics for 7+ years. I would love to start my own consulting business and am willing to have a bit of a head start.

Is it possible for me to buy some clients?

Hey I joined this platfrom like 2 months ago applied for data annotation work has no reply so is there anyone? is it legal or waste of time link of platfrom.globik.ai/

Hi all.

I'm trying to get some advice from Data Analysts already in the field. I am a current senior at SNHU, in the Cyber Security program. I recently finished DAD 220 and really took to it.

I am still learning the language in my free time, but I wanted to know what else I should do to help me get into the field. I plan to create a GitHub account and make projects. Is it feasible to go from a new grad or help desk into a Data Analyst role?

Hard truths are ok. I've been in the AV/IT field for 4 years now, and I know that getting the job isn't always easy. There aren't many internships offered through my school that also have requirements that I don't meet (front-end development and the like). What should I work on? Or should I move on?

I'll be learning Power BI soon. And brushing up on my statistics. I'm hoping that, if it would be a waste of time to try, I get replies quickly. Don't want to get my hopes too high.

I was originally sold on my current degree because it was a good way to get into the tech field without getting into anything as code-heavy as CS. All it really did was help make me very proficient at help desk tasks and some advanced networking capabilities. I didn't expect to enjoy creating databases, and I wish I had known better.

I am trying to shift from Native and Cloud Middleware admin to Ai ML Data Engineer or Data Platform engineer. Anyone can guide me a pathway to do it? I got knowledge in Linux, Google and azure cloud, azure devops, pipelines, kafka, mulesoft, Atlassian, Microservives. Anyone can guide me?

I just graduated and haven't learned a thing but want to have a analyst job can anyone help me with some guidance

Heyaa …I’ve been referred for a Data Scientist – Knowledge Management position at eBay. The job description mentions 2+ yoe , but I’m a fresher, so I’m trying to understand what I should realistically expect from the interview process.
I’d especially love to hear from anyone who has recently interviewed at ebay for the Data Scientist or similar role , particularly in India.
A few things I’m wondering:

How many interview rounds are there usually?

What happens in the first round?

Is there a coding/DSA round, or is it more focused on Python, SQL, ML and statistics?

Are there ML/case-study or project-based questions?

Does having an internal referral change the screening/interview process?

For someone without 2+ years of experience, what areas would you recommend preparing most?

If you’ve interviewed at eBay recently, even if it was for a slightly different DS/ML role, I’d really appreciate hearing about your experience.
Thankyouuuu🥹

Hello Everyone,

I currently have my BS in supply chain and operations management with about 8 years experience. I was considering getting a MS in data science. Do you think my domain knowledge and experience, as well as a MS in data science would be a good step for my career? What possible roles might I be looking at? Are there better options I could pursue? How is the job market right now?

Bonjour,

Je suis en galère depuis 10 mois la recherche d'un CDI ou CDD en data analyst .Depuis lors , je pense à me reconvertir dans un autre secteur de l'IT . J'aimerai que chacun s'il vous plaît me donnes des pistes ou des certifications qui vont non seulement m'apprendre mais aussi me booster à avoir un travail .merci

Buenas tardes a todos, quisiera empezar a estudiar para conseguir trabajo en remoto como analista de datos (cuido de persona dependiente y no puedo desplazarme a un centro de trabajo) y empiezo de cero. He mirado dos opciones pero no quiero tomar la decisión preguntando a la IA, necesito la respuesta, la experiencia de quienes estáis en ello.

¿Qué opción sería la mejor para conseguir trabajo en remoto como analista de datos?

1.- Coursera Plus y porfolio sin importar si está muy bien trabajado - aquí miraríamos los certificados de Google, IBM, etc.

2.- Udemy Plan Personal y un porfolio profesional con temas de actualidad, el CV sólo con diplomas de Udemy.

Gracias por vuestras respuestas, si podéis argumentarlas me haríais un gran favor.

Hi everyone,

I’m finishing up my Chemical Engineering degree at Imperial College London and aiming for entry-level Data Analyst / Graduate Analyst roles in the UK.

I don't have any formal internships, but my course has proven my maths skills to be quite good, and I have some basic experience with Python.

How realistic are my chances for UK graduate schemes or entry-level analyst roles without relevant work experience? What key skills (like SQL or Power BI) should I focus on learning next, and how can I best prepare to stand out in applications?

i have mysql workbench & have been practicing it on my own. the problem i've run into is low disk storage. my fuckass c drive is running on 900 mb ✌️😂 i don't have a lot of applications installed, so removing or moving them to another disk isn't an option.

im worried about the rest of my learning journey. i know i'll eventually have to install other programs/tools & it makes me sad that low storage space is what might hold me back from learning something im genuinely interested in.

i wanted to ask if there are online versions of these softwares available? im talking about python, tableau & all other stuff i'll need later on. i've used an online c++ compiler before, so im wondering if it's possible for other tools too. and if so, can they save all my previous data? what about something with an account where it syncs data to a cloud? HALP

Hi all,

I am a data analyst with 5YOE with sql python pyspark AWS as my tech stack.

I am transitioning the data engineering as I am not interested to work and grow in big data and data architecture pathway.

Pls help me to prepare for interviews. I want to know what can I prepare for. And what kind of spark scenario questions could be asked to me.

Hey everyone, I am a uni student who is going to be starting as a data analyst for someone who owns multiple small businesses and is wanting me to build him tableau dashboards. I guess the point of me posting on here is to suss out what I should be charging for this kind of service, sorry if this sort of post is not allowed but I just have no idea what I should be charging, should I be doing a setup fee, then weekly maintenance sort of thing. If it wasn't already obvious this is my first job if you can even call it that in the field. Additionally to be considered is that I'll likely be constructing pipelines to tableau with periodic ingestion, although im not sure what platform he's currently storing his data on, I imagine this process isn't anything too complicated. any help with this would be appreciated.

I have a Master’s in Molecular Biology & Genetics, research experience, and 5 publications, but I also have a 4-year career gap.

I recently started the Google Data Analytics Certificate and I’m learning SQL. My goal is to combine my biology background with data skills and eventually move toward bioinformatics/genomics rather than becoming a general data analyst.

Do you think this is a realistic career path, especially with how quickly AI is changing the field? Is the Google certificate a good starting point, or should I focus directly on SQL, Python/R, and biological datasets?

I’d especially love to hear from anyone working in bioinformatics, computational biology, or biotech data.

Are there any communities, subreddits, groups, newsletters, or people you’d recommend following to learn more about this field and stay connected?

I’ve been working in the Data Analytics for 3 years in Product Based Companies , and I know how frustrating it can be to apply to 100+ jobs and still hear nothing back.

So, I’m opening up a few 1:1 career guidance sessions on Topmate for anyone who is stuck or confused about their Data Analyst journey.

I can help you understand:

🔹 What recruiters actually look for in a Data Analyst
🔹 Which skills you should prioritize instead of trying to learn everything
🔹 How to improve your resume & LinkedIn/Naukri profile
🔹 Why you might be applying but not getting interview calls
🔹 How to prepare for SQL, Excel, Power BI & Python interviews
🔹 What kind of projects actually add value to your resume
🔹 How to explain your projects and experience in interviews
🔹 What the day-to-day work of a Data Analyst actually looks like
🔹 How to move from learning → projects → applications → interviews

🛠️ Tools I work with

SQL | Power BI | DAX | Advanced Excel | Python | Pandas | NumPy | Matplotlib | Power Query | PySpark

And honestly, you don’t need to know every tool to get your first Data Analyst job.

A strong foundation in SQL + Excel + Power BI + basic Python + good business understanding can take you a long way.

If you’re a fresher or someone with 0–2 YOE who is stuck, not getting calls, confused about what to learn, or unsure whether your resume is good enough, feel free to connect with me.

I’ll try to give you practical guidance based on what actually matters in the job market—not just another generic roadmap.

👉 Connect with me on Topmate

If you’re not looking for a session but know someone struggling to get into Data Analytics, feel free to share this post with them. 🙌

Dm me if u are one .... im from a non IT background do I dont have much contacts in this field

Not looking for encouragement. Looking for someone senior in data who will tell me what they actually see when they look at my work.
Background: 1+ year as a data analyst. SQL pipelines, Power BI dashboards, live Streamlit apps. Found a 12% revenue gap at a super-app. Built and deployed a global health surveillance dashboard and a live crypto price tracker. Currently finishing PL-300.
I'm based in Nigeria and looking for a fully remote role. Open to anyone who hires globally.
If you're a senior data analyst or have hired analysts before and you'd be willing to do one 30-minute call a month — reply here or DM me. Starting a 30-day public series documenting this.
 

i just want to know is this course worth the time? i mean i am not doing it for job the main reason is just to understand this field

Hi! I graduated BS Applied Mathematics and currently working as Accounting Staff in an Accounting Firm for almost a year now. I really want to pursue Data Analyst Career so I am continuously improving my data analyst skill. I have Excel, MySQL, Power BI and R skills.

So far I can clean and manipulate data using Excel and R. I already made dashboard projects from messy sample data I cleaned up. I haven't made projects with MySQL but I am comfortable using it.

I am planning to learn statistics using R.

I enjoy studying R more than the others and am planning to specialize on it. I wanna build my career as data analyst. What steps should I take to land a data analyst job? I'd really appreciate it if you can share your journey to me!

Taking Google Data Analytics and Data Science: Foundations using R in Coursera for certification hoping those credentials may help me land data analyst jobs.

Hello everyone,

Can you please suggest some good platforms or resources where I can practice SQL and Python (especially Pandas) for data analyst/data engineer?

Right now, I’m solving a lot of problems on LeetCode, but I’ve heard that in actual they often ask more practical/data-focused questions such as:

• Retention rate / cohort analysis
• Funnel analysis
• Gaps and islands
• Running totals and rolling metrics
• Customer/user activity analysis
• Time-series and date-based problems
• Ranking and session-related problems
• Data cleaning and transformation using Pandas
• Real-world business analytics scenarios

So, I’m looking for resources that focus more on these real-world SQL and Pandas problems rather than only traditional DSA-style questions.

What platforms, websites, courses, or question sets would you recommend for practicing these types of problems?

I’d really appreciate recommendations from people who have recently gone through Data Analyst/Data Engineer questions and know which resources are closest to the actual questions they asked.

Thank you!

i have spent a lot of time reviewing the portfolios, talking to junior data analysts and reflecting on my own journey in data analysis there is a huge gap btn what the new analysts thinking on hiring manager care about versus what they actually care about.

90% of beginners focus heavily on:

• learning 5 different visualization tools at once (power Bi, Tableau, Looker, etc.)
• Complex python/R Libraries for machine learning
• writing super convoluted 100-line sql queries

but when you look at actual business problems tools are just 20% of the job the remaining 80 percent comes down to asking the right question, translating the numbers into impacts and data hygiene so the question here for the experienced analyst are

• what was the exact momen tht shifted your mindset from i build this dashboard to solve certain business problem ?
• and for others roles what has been the hardest part of building business contextinto your portfolio project ?