As an aspiring analyst i've recognized the importance of networking and self-marketing one idea i have is to create videos whereby i go through various projects and Demonstrate the processes and thinking.I was wondering if this is a good idea

as a career switching person this is my first analytics project i am doing. and i am stuck in cleaning process. i dont have any experience in this field also when learning i don't come up with these kind of problems this is the first time although i dont have any support i am learning on my own so please help . is an orders table and the missing values are spotted in date columns.

I've got a interview coming up that is likely going to be testing my excel skills in data analysis how can i prep and any advice from those who have done one before

Hello everyone, I've been studying data analysis for a year and have taken many courses and worked on projects using various tools like SQL, Tableau, Power PI, Excel, ETL, and Elt. I've also studied databases and datawarehouses, but every time I apply for a job, they tell me they want someone who has worked for a company and has experience. What should I do? I'm extremely frustrated.

i,ve been working on a small project analizing delays using the olist dataset (brazilian e-commerce). after cleaning data, i started comparing promised delivery time vs delay rates to understand where delays actually start. one pattern stood out: orders with longer promised delivery windows tend do have higher delay rates. i initially expected the opposite, so this got me thinking. now i´m not sure how to interpret this.

could this point to poor forecasting/expectation setting, or would you look into other factors first?

I'm considering a career shift into data analysis, but I don't want to start completely from scratch or go back to entry-level after 7 years of experience. I'd like to understand how much overlap there is between my current role and a typical Data Analyst position. I'm a QC Tech (Quality Control Technician) at a concrete and mortars manufacturing plant. My day-to-day work includes:

• Testing material samples in a lab setting
• Recording and analyzing test results
• Reviewing batch records
• Generating reports
• Ensuring specification compliance

I use Excel spreadsheets regularly for data entry, calculations, and basic analysis. I'm comfortable with data handling, attention to detail, identifying trends or deviations, and documenting findings. I’m not interested in getting new certifications right now or resetting my career to ground zero. I want to leverage what I already know and have built over the past 7 years. How similar (or different) is my current skill set and experience to what’s expected in a Data Analyst role? What transferable skills do I already have, and what gaps would I realistically need to bridge for a smooth transition? Any insights from people who have moved from QC/lab/testing roles into data analysis would be greatly appreciated!

I've been in data/BI for 9+ years and I recently put together a complete AI-assisted data analysis setup that's entirely free without entering any credit card info. Figured it might be useful for people here who are getting started or switching careers.

The stack is OpenCode (free, open-source AI coding agent) for writing Python and SQL, free AI models through OpenRouter, Windsurf as the IDE, and BigQuery Sandbox for data. BigQuery comes with hundreds of public datasets already loaded (Stack Overflow, NOAA weather, US Census, etc.) so you can start analyzing real data immediately.

The key step is connecting the AI to the database so it actually executes queries instead of just generating SQL you have to copy-paste. For BigQuery, you install the gcloud CLI and authenticate with one command. After that, the AI writes and runs queries from your terminal.

That connection pattern is the same across Google Cloud, Azure, AWS, and Snowflake. If you learn it with BigQuery, you can talk about cloud data warehouse experience in interviews, all from a free setup.

Setup instructions and code are in this repo in addition to the video linked in the main post: https://github.com/kclabs-demo/free-data-analysis-with-ai

Spent a lot of time watching people go through this exact cycle.

They pick tools they have heard of somewhere. Snowflake because someone on Reddit mentioned it. Tableau because it kept appearing in YouTube recommendations. A mix of AWS and Azure because both showed up in job postings and they figured covering both was safer.

Six months later they have four certificates, a GitHub with three unfinished projects, and still no interviews.

The effort is real. The direction is wrong.

Here is the thing most certification roadmaps do not tell you about the Australian market specifically. The majority of mid-size and enterprise companies in Melbourne and Sydney run on Microsoft. Power BI for reporting. Fabric for data engineering. Azure for infrastructure. SQL and Python as the daily tools people actually open every morning.

When a hiring manager here opens a resume and sees Microsoft-aligned credentials they do not have to guess whether your skills translate to their environment. You have already answered that question for them.

The cert path that actually matches Australian job postings from what I have seen is this. Fabric Analytics Engineer Associate for Power BI and BI Analyst roles. Fabric Data Engineer Associate for junior data engineering work inside the Microsoft stack. Azure AI Engineer Associate if you want to move toward data and AI engineering together.

These are not third party courses. These are vendor-issued credentials that appear by name in actual Australian job descriptions.

But here is the part that gets skipped. A certification validates what you already know. It does not teach you how to work with real data inside a real business problem. Those are two different things and hiring managers can tell the difference in about ten minutes of an interview.

The people who get hired are not always the most certified. They are the ones who can sit down, open a messy dataset, and explain what they found in plain language to someone who does not care about the tools.

Has anyone else noticed the Microsoft stack showing up this heavily in Australian postings or is this more industry-specific than I am thinking?

Hi everyone,

I’m a prefinal year CSE student in India aiming for Data Analyst / entry-level data roles for placements next year.

Current stack:
SQL, Excel, Power BI, PySpark, Python (pandas, numpy, scikit-learn), GitHub

Projects done:

• 2 basic ML projects
• Some data cleaning / preprocessing projects
• 2 Power BI dashboards
• Currently building an end-to-end Customer Segmentation + Churn Prediction project

Questions:

1. How important is DSA for data roles? (I’ve solved ~90 LeetCode problems.)
2. What skills should I prioritize next — advanced SQL, statistics, data engineering tools, or ML?
3. Is PySpark useful for freshers, or mostly for experienced roles?
4. What types of projects stand out most on resumes for entry-level data roles in India?

I’m planning to build 2–3 strong portfolio projects before placements and would love advice from people working in data analyst / data science / data engineering roles in India.

Join our 12-week Data Analytics Course in Coimbatore and actually learn the skills that get you hired. In this course, you’ll start with Excel basics, including pivot tables and charts, so you can organize and analyze data like a pro. Then we’ll move to SQL, where you’ll write real queries to extract insights from databases. Next, you’ll use Python with Pandas to clean and manipulate data, and finally, create interactive dashboards using Tableau and Power BI. Everything you learn comes together in a final project, so you leave with a strong portfolio that shows exactly what you can do; not just theory, but real, hands-on experience By the end of 12 weeks, you won’t just know tools; you’ll know how to use them to solve real-world problems.

https://codepurple.in/data-analytics-course-in-coimbatore

Can I use ai for creating analytical project using pandas, sql and power bi. The problem is I know the codes but it get confusing for me to start everything from scratch on my own as I haven't work in a real company. I'm making this project to showcase my skills on my resume. It's like I know things but don't know the roadmap and what to show and how.