When I first started learning data analytics, I felt a little lost. There are so many tools out there and everyone seems to have a favourite. Should I start with visualization tools? Learn SQL first? Try everything at once?
I decided to take it step by step. These are the tools I have been working with so far and how each one has helped me grow.
Power BI: My First Real Dashboard
Power BI was the first tool that really clicked for me. I spent time creating dashboards, trying different visuals and using DAX to build calculated fields. After experimenting with multiple projects, building dashboards started to feel natural and I could see myself improving with each one.
What I have done with Power BI
- Built dashboards to track revenue and cart abandonment
- Used DAX to create calculated fields and KPIs
- Added interactivity with filters and slicers
Power BI has been my starting point for turning data into insights. It helped me understand not just how to show numbers, but how to tell a story with them.
Starting with Power BI gave me the foundation to think about data in a structured way. It is where I began to feel confident in creating something useful out of raw data.
Snowflake and MySQL: Learning to Look Behind the Dashboards
Working with visualization tools made me curious about what happens before the data even reaches them. My first experience with SQL was actually in Snowflake. Many people might think starting with MySQL is the obvious path because it is widely known and has countless beginner tutorials. But as a beginner, Snowflake felt just as approachable. There was no complicated setup for me to get started and I could begin writing queries right away.
Snowflake does come with a lot of extra features meant for large scale cloud data management, but as someone just starting to write SQL, those advanced features did not get in the way. In fact, starting with Snowflake turned out to be a good decision because it is so deep. On one platform I could not only learn SQL but also get exposure to concepts like virtual warehouses and structured environments, which gave me a broader view of how data can be handled at scale.
Later on, I explored MySQL. Coming to it after Snowflake felt very natural and straightforward. Practicing joins, filters and aggregations in MySQL helped reinforce the fundamentals I had already built.
I have also worked with Databricks, though not as extensively as Snowflake. It gave me another angle to think about data processing and how SQL can fit into different platforms.
Things I have practiced
- Writing queries to pull and filter data
- Joining tables to combine datasets
- Aggregating and grouping data for analysis
How I Keep Learning
Using tools is one part of the journey, but learning itself never stops. I have been taking in knowledge from many sources. LinkedIn Learning courses helped me build a base. YouTube videos gave me practical demonstrations of concepts. I joined a few bootcamps to go deeper into specific areas. Most importantly, I have reached out to people already working in the field. A simple conversation sometimes brings up a new term or concept I have never heard before.
Whenever that happens, I make a note of it. Later, when I have some time, I look it up and learn at least the relevant parts. Sometimes that small effort of exploring a new word or idea opens up a whole new area for me.
Learning this way has taught me that progress does not always come from big leaps. It often comes from small, consistent steps forward. I remind myself of a line I once read: The capacity to learn is a gift; the ability to learn is a skill; the willingness to learn is a choice. Every time I feel stuck, these words push me to keep going, to stay curious and to keep building on what I know.
Theoretical learning is just as important as practical work because it gives depth to what you are doing. A dashboard might show numbers, but understanding the concept behind them makes those numbers meaningful.
Wrapping Up
Power BI helped me build a foundation in visualization. Snowflake pushed me to learn SQL in an environment that goes far beyond basic querying, while MySQL strengthened my fundamentals in a simpler setup. Exploring Databricks added yet another layer of perspective to how data can be managed and analyzed.
If you have been in data for a while, I would love to hear what tools you started with or what you think beginners should try next. And if you are just starting out, I hope this gives you some ideas on where to begin.
Thank you for reading my second blog. Your support really motivates me to keep going.