NURAI LAB

25/09/2026

Our students presenting the dashboards they created with Power BI — transforming raw data into clear, interactive insights. 📊

From learning the tools to presenting their analysis, our students are building practical data analytics skills.

25/09/2026

Watch how our students learn how to use DAX in Power BI to create calculated columns, measures, and dynamic calculations for deeper data analysis. 📊

Building practical Power BI skills for real-world data analytics.

Ready to build your data analytics skills? Follow NuraiLab and join us on the journey from learning to practical application.

24/09/2026

Our students are learning how to use SQL to query databases, filter data, sort results, and extract the information they need for analysis. 💻📊

Practical SQL skills for real-world data analysis.

24/09/2026

Our students are learning how to create clear, interactive dashboards using Power BI. 📊

Building practical data analytics skills, one project at a time.

04/09/2026

03/09/2026

A slow SQL query doesn't always mean you need a more complicated query. Before rewriting everything, investigate why it's slow.

03/09/2026

Don’t stop at WHAT happened.

Imagine your report shows that revenue dropped by 20% this month. A beginner might simply report, “Revenue decreased by 20%.” But an analyst knows that this is only the starting point.

Ask yourself: What exactly dropped?
Was it the total number of customers, number of orders, average order value, a particular product, or sales from a specific region?
Then break the numbers down. Maybe customers only dropped by 5%, but the average amount spent by each customer dropped significantly.

That tells you the problem may not be about losing customers it may be about customers spending less.
Next, identify where the biggest change occurred.

Perhaps most products performed normally, but one major product experienced a 45% decline. Now you have a stronger direction for your investigation.

Don't forget to compare the current results with previous months or the same period last year. A decline might look alarming until you discover that the same decline happens every year during that particular period.

The goal isn't just to tell people what happened. It's to understand what is behind the number.

That is how you think like an analyst: don't stop at the first answer. Keep asking questions until the data starts telling you the full story.
Nurai lab - Enlightenment through intelligence.

02/09/2026

Here is why curiosity is your greatest tool as a data analyst 👇👇

02/09/2026

Can someone be a good data analyst without knowing Python?
🔘 Yes
🔘 No
🔘 Depends on the role

Drop your response in the comment section