BLOGS
I still remember the first time I had to present data in a university
class - my professor was there, along with a lot of my classmates. I had a beautifully detailed dataset,
and what I thought was a well-prepared presentation. But when I put my charts on
the screen, I could see the confusion on everyone's face. The number was there, but the story was lost.
Studies find that data analysts spend up to 80% of their time cleaning data before they can even begin analysis.
Messy, incomplete, and inconsistent data slow down workflows, introduce errors and often lead to poor model performance.
Despite its critical role, data cleaning remains a tedious and repetitive process.
What if a tool could automate it?
Imagine this - You open Netflix, scroll through your recommendations, and a striking movie thumbnail catches your eye. Without thinking twice, you click on it.
But did you know that Netflix has tested multiple versions of that thumbnail before deciding which one to show you?
Let’s say we’ve just received a new dataset. And as expected, it’s messy, overwhelming, and full of numbers that don’t seem to tell a clear story.
As data analysts, our job is not just about crunching numbers, it’s about transform that chaos into valuable insights.
But how do we make sense of raw data and turn it into something actionable?
It’s all start with mindset.
