“Data analyst” sounds abstract — until you see what one actually does week to week. In practice it’s one of the clearest and most in-demand jobs in IT, and one of the most accessible to start from scratch.
What an analyst does every day
An analyst’s work is a four-step cycle:
- Gather data — pull the right tables from a database (this is where SQL comes in).
- Clean it — real data is always messy: missing values, duplicates, typos.
- Find patterns — compute metrics, compare segments, spot a trend.
- Tell the story — build a dashboard or report the business can understand.
An analyst’s value isn’t the tables — it’s the decisions made on the back of them.
The skills you need
- SQL — the query language for databases, core tool number one.
- Python (Pandas, NumPy) — processing and analyzing data that won’t fit in Excel.
- Visualization (Power BI) — turning numbers into clear, interactive dashboards.
- Statistical thinking — telling randomness apart from a real pattern.
How to learn it from scratch
You don’t need to learn these skills separately over years. On the Data Analysis course you go from Python and data wrangling to dashboards and business metrics, working with real, messy datasets — exactly what you’ll meet on the job. The Power BI course then deepens visualization and DAX to a level employers value.
Where to grow next
Analytics is a great entry point that opens several paths: BI specialist, product analyst, and later data scientist. Starting from clear metrics and dashboards, you build up complexity step by step.