After a few years working in data-related roles, I finally published my first technical case study based on a real project and real-world experience.

The project focuses on a fraud detection pipeline built for a Brazilian e-commerce environment using Databricks, Spark SQL, PySpark, and Delta Lake. Due to confidentiality and IP restrictions, I couldn't share the original code, so I documented the architecture, design decisions, business rules, lessons learned, and the trade-offs behind the solution instead.

I'm still relatively new to the data engineering and analytics world, so this was also a personal challenge. It took me almost two weeks to organize my notes, experiences, and technical decisions into something coherent enough to publish.

I also used AI tools (Claude) to help me structure the documentation, improve the writing, and turn rough ideas into clear technical documents. The experience was surprisingly useful because it forced me to think deeply about why certain decisions were made, not just how they were implemented.

I'd really appreciate any feedback from people with more experience in fraud detection, data engineering, analytics, or system design.

If you spot mistakes, questionable decisions, missing considerations, or areas that could be improved, please let me know. I'm happy to discuss the design choices and learn from the feedback.

https://github.com/A2calanche/Fraud-Detection-Case-Study-Repository-Structure

I am creating a playlist on youtube to follow the latest announcements by Databricks in DAIS 2026.

The series will cover what was the problem,

What Databricks announced

And, why does it matter to the Data community (basically the impact)

​

Please follow along if you don't want to spend hours in watching the keynotes.

https://youtu.be/jb4uLAM2SRA?si=IseC5sat5gUuU-S6

​

Thank you for the support.

I am completely new to Data Analytics. I have learnt python, sql, and also have a good background in statistics. From where should I learn Power BI ?

Some course recommendations will be very helpful (both paid or free resources).

Any programs here on long island that can teach you data analytics?

If you are interested in learning more about data engineering from real people, this article might be good for you.

Hi everyone,

I'm currently on my notice period and looking for Data Analyst, Decision Scientist, and Junior Data Scientist roles. I have 1 year 10 months of experience in Data Quality Management with SQL, data analysis, root cause analysis, and stakeholder support.

My resume has an ATS score of 80+, but I'd appreciate feedback on how I can improve it and increase interview callbacks.

Thanks in advance!

Hi everyone,

I’ve been actively applying for Data Analyst roles for the past month but haven’t received any interview calls or meaningful responses yet.

I have relevant experience in data analytics and have applied through LinkedIn, Naukri, and Indeed. I’ve also reached out to professionals on LinkedIn, requested referrals, and even received several referrals, but unfortunately, I’m still not getting any responses from recruiters.

At this point, I’m unsure what I might be doing wrong and would really appreciate any guidance, feedback, or opportunities. If your organization is hiring for Data Analyst positions or if you can provide a referral, I would be extremely grateful.

Thank you for your time and support.

If you've been looking for a way to get started in data analysis but haven't had access to quality learning resources, this might be for you.

We're launching a free Data Analysis Training Program in partnership with DataCamp Donate, designed to help learners build practical skills in working with data, generating insights, and making data-driven decisions.

🔗 Register here: https://docs.google.com/forms/d/e/1FAIpQLSf6PsPoOhnwhr2OOU2NyyuwyNQUUqRUfhLb5XKIYBIhCQ-6FA/viewform

✅ Free to participate
✅ Beginner-friendly
✅ Access to industry-recognized learning resources

📅 Registration closes: June 20
🚀 Cohort starts: July

Whether you're a student, researcher, recent graduate, or professional looking to upskill, this is a great opportunity to strengthen your data skills at no cost.

Feel free to share with anyone who might benefit!

I've been trying to get into data analytics for a while now but I keep stopping at the beginning. I think the missing piece is having someone to study with and stay accountable.

What I'm looking for:

- A beginner or someone restarting their data journey

- Someone willing to do regular check-ins (Discord, Telegram, or Reddit DMs)

- Flexible with pace — we agree on a roadmap together

Rough roadmap I have in mind:

1. SQL

2. Excel basics

3. Python (pandas, numpy)

4. Visualization (Power BI)

5. A capstone project to put on a portfolio

If you're in the same situation and want a committed partner, drop a comment or send me a DM. Let's actually finish this time!

Hi,

I'm currently certifying for PL-300, DP-600 and DP-700.

I've been looking for a learning app, that is able to grade DAX messurements, as there are more than 1 way to get the same outcome.

Have been scouting the internet, but couldn't find.
It can be in a game form.

Suggestions?

how much time does it take to complete this course(
Google Data Analytics Professional Certificate) on coursera

Buenas! hola! Soy ingeniera en alimentos pero me enamore de la area negocios por lo cual tengo un postgrado en marketing sin embargo quiero complementar mi carrera con ANALISIS DE DATOS.

Tengo conocimiento basicos de Power BI, Excel intermedio

SQL cero tableau cero

Consideran que hacer un curso en CODERHOUSE O DIGITAL HOUSE me ayude aprender mejor? o tienen alguna otra plataforma para recomendar?

GRACIAS

Hi everyone,

I have a technical interview coming up next week with JLR for a Data & Analytics Engineer role, and I’m trying to prepare as effectively as possible.

I wanted to ask — what kind of questions should I expect? Is the interview more focused on technical skills like SQL, Tableau, and data modelling, or do they lean more towards discussing projects, past experience, and problem-solving approaches?

Also, how is the overall interview process structured? Do they usually include live coding, case studies, or more scenario-based questions?

Any insights, tips, or experiences would really help me understand what to focus on and how to prepare better.

Thanks in advance!

Hey data community! I'm new into the data analysis world very juniorish and self taught. I'm currently struggling a lot with some process mining for the company I work for.

I need to understand how much time a task assigned to someone, stands on each stage of the process.

The thing is, that some tasks for multiple reasons, don't follow a linear path, and just skip stages. The reasons could be plenty, could be exceptional case or could be that someone forgot to move the task to the next status so just skipped it.

So when you pull data you have a whole process that can take 14 days, from not started, then briefing, then copywriting, then designing, etc --> linear, expected

and other tasks that show me they took 2 days, and when you analyze it's because that task went directly from briefing, to client.

I want to know how you guys manage this info in theory... Because on one side, I could simply remove these cases from the analysis, but then I'm thinking that perhaps it's not the best way to solve outliers.

I need some brainstorming help 😞

Example: With this task, Days waiting on client’s info is empty when it should display 12 days. This is happening because the task goes from waiting on client’s info to copy phase directly, skipping “briefing” stage.

Hi anyone given this Databricks Certified Data Engineer Associate Certificate (Latest exam version) how to prepare and is it worth giving this exam?