How to stand out as a Data Analyst

Back in my days working with data analysts, the favorite part of the job was when we discussed outlier use cases that needed explanation. We would trace back these cases and build our story step by step, one table at a time, each table transformed from a previous one and giving us insights.

This was the favorite part of all the data analysts. They all used to login and start filtering tables. It was the only situation where you would see all of them simultaneously and eagerly writing SQL queries!

All the excellent data analysts I worked with had one common trait:

Good investigators and storytellers

This skill doesn't come instantly. They trained their analytical muscles over time. The more you do it, the more you will enjoy it and get better at it.

Anyone can learn to write SQL code and generate graphs - those are just tools and means that can be taught. But being able to tell the story from the graph, being able to trace backwards and build the story one step at a time - that's what's gonna make you stand out!!

Let's do an example together

Imagine this scenario: The Director of Operations has noticed an alarming increase in product returns over the past few months, particularly in certain product categories. The return rate jumped from a steady 5% to over 12% in some regions, particularly Northwest. This is costing the company significant money in shipping, restocking, and customer service resources.

Let's build our story

We start by asking the right questions and digging deeper with each answer we find.

Question 1: What is the return rate by product category and region over time in 2023 in Northwest?

We see an unusually steady high return rate for Smart Home Devices in the Northwest region starting in August 2023. This stands out from all other categories and regions. Now we need to understand why.

Question 2: For Smart Home Devices returned from the Northwest region after August 2023, what are the most common return reasons compared to other products?

Compatibility issues okay, but Device not working properly?? This is unusually high compared to "Changed mind". This suggests there's a technical issue with these specific devices. Where did we order them from?

Question 3: What is the return rate for each manufacturing batch of Smart Home Devices in the Northwest region after August 2023?

We found the culprit! Batch "SH-2023-07B" has a dramatically higher return rate (around 42%) compared to other batches. This is where our investigation gets interesting.

Question 4: What is the relationship between humidity levels and return rates for Smart Home Devices by manufacturing batch?

We know that these home devices are controlled by humidity sensors and looking at environmental factors, we discover that batch SH-2023-07B failures correlate strongly with high humidity levels (above 75%), while other batches perform well even in high humidity. This is the connection we've been looking for!

Question 5: What are the humidity tolerance specifications for different manufacturing batches of Smart Home Devices?

Okay, now we have our answer! Batch SH-2023-07B was manufactured with components rated only for "Up to 75%" humidity, while other batches can handle "Up to 95%" humidity. The mystery is solved.

The story goes as follows

1. Manufacturing batch SH-2023-07B used a different supplier for humidity sensors
2. The technical specifications show this batch's sensors degrade rapidly in humidity levels above 80%
3. The Northwest region experienced unusually high humidity in late summer 2023
4. The product documentation failed to warn users about humidity limitations

The Director of Operations puts it together

1. A cost-cutting decision changed component suppliers for a specific manufacturing batch
2. Quality control missed that the new sensors couldn't handle high humidity
3. An unusually humid season in the Northwest region exposed the defect
4. The product documentation lacked proper environmental guidelines

The damage

• Approximately $1.2M in return costs
• Customer satisfaction in the region dropped 14 points
• Brand reputation damage specific to the product line

The Solution

• Recall the affected batch
• Update product documentation
• Implement additional environmental testing
• Add humidity sensors to the quality control process

You were the hero of this story!!!! You followed the data, asked the right questions, and uncovered the truth. And you are now indispensable!!!

In Summary

Data storytelling is the difference between just analyzing numbers and driving real business impact. Follow the data trail, connect dots that others miss, and become a business detective who saves his company millions.

And the best part? Great storytellers get noticed. Leadership seeks you out, your network expands, and your career accelerates. People don't just want your analysis—they want your perspective. That's how you become truly indispensable.

All the visualizations in this post were created using PlotsALot, an AI specifically trained for data analysis and visualization. Try it and start building your own data detective stories!