When I first heard about data analytics, I imagined huge spreadsheets, complicated charts, and lots of confusing code. It felt like something meant only for tech experts or math geniuses. But after slowly getting into it, I’ve realized that data analytics is really just about using data to understand what’s going on and to help make better decisions.
So, what is data analytics?
To put it simply, data analytics is the process of looking at data to find patterns or answers. It helps people and businesses understand things like why sales went down, what customers like the most, or how to improve something.
Different types of data analytics
There are four main types that I’ve learned about so far:
Descriptive Analytics
What happened?
It’s about summarizing past data. For example, “How many orders did we receive last month?”
Diagnostic Analytics
Why did it happen?
It digs deeper into the data to understand the causes, such as “Why did sales drop last quarter?”
Predictive Analytics
What is likely to happen?
It uses past data to forecast future outcomes. For instance, predicting next month’s revenue based on trends.
Prescriptive Analytics
What should we do about it?
It suggests actions based on predictions. For example, “Which product should we promote to boost sales?”
Right now, I feel pretty confident with the first two. They’re more about understanding past data, and that’s where I’ve spent most of my time learning. I’ve started exploring the other two as well, but I still have a lot to learn there.
How I’m learning
I’ve been practicing with real datasets and using different tools depending on what I’m working on. For example, I often use Power BI and Tableau to build dashboards and explore ways to visualize data. For cleaning and organizing smaller datasets, Excel has been really useful.
I’ve also started learning how to write basic queries using MySQL, which is helping me understand how data is stored and accessed. Along the way, I’ve got familiar with tools like Snowflake and Databricks, just to see how they fit into larger data workflows. I’m slowly building my understanding across different tools.
Why I’m writing this
I wanted to write this as a way to organize my thoughts and maybe help someone else who’s just starting like me. I know how overwhelming it can feel at first. You don’t need to know everything right away. Just start small, stay curious, and keep learning bit by bit.
Thanks for reading!