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# The Journey Behind Mitzu.io
I’m István Mészáros, and in February 2023, I founded Mitzu.io with a clear mission: to help businesses unlock the full potential of their data. But it isn’t just a product—it’s the culmination of years of experience, countless frustrations, and a deep desire to challenge the third-party tools. This is the story of why I started.

## The Problem That Wouldn’t Go Away
Over the years, I’ve worked with many companies trying to make sense of their data. Like most people in the industry, I’ve seen how important analytics is for decision-making. But I’ve also seen how messy and inefficient it can be.
The rise of modern data warehouses like Snowflake, BigQuery, and Databricks promised to change everything. These platforms made it easier than ever to store and manage large-scale of data. But when it came to actually analyzing that data, businesses were stuck using tools that hadn’t evolved with the times.
Here’s what I mean: most analytics tools require you to copy your data into their systems. This duplication creates all kinds of problems:
- **It’s expensive** - Costs skyrocket as your business grows.
- It’s slow—data is **never truly up-to-date** because of delays in syncing.
- **It’s complicated** — You need engineers to set up and maintain reverse ETL pipelines.
- **It’s risky** — Moving sensitive data into third-party systems increases security concerns.
It felt like businesses were being forced to work around the limitations of these tools rather than having tools that worked for them. And no matter how much effort we put into fixing these inefficiencies, the root problem remained: the tools themselves weren’t designed for this new era of data infrastructure.

## The Turning Point
The idea for Mitzu.io didn’t come from a single “eureka” moment—it came from years of working through these frustrations. However, a specific project pushed me over the edge.
I was helping a company integrate multiple analytics tools with their data warehouse. The setup was a nightmare: syncing data between systems, dealing with inconsistencies, and constantly troubleshooting errors. At one point, I remember thinking: Why are we even doing this? Why can’t we analyze the data directly where it already lives?
That question stuck with me. And the more I thought about it, the more obvious the answer became: we didn’t need another tool that copied data - we needed a tool that worked directly on top of the data warehouse itself.

## A Vision for Change
With this vision in mind, I set out to build Mitzu.io. But this wasn’t just about solving technical problems—it was about addressing a deeper issue: the disconnect between how businesses store their data and how they analyze it.
I wanted to create something that:
- Eliminated unnecessary duplication by working directly within existing data warehouses.
- Made analytics accessible for non-technical users without requiring SQL expertise.
- Provided real-time insights so teams could act quickly on up-to-date information.
- Reduced costs and complexity by cutting out reverse ETL processes and external systems.
It wasn’t easy. There are plenty of moments where I questioned whether we could pull it off. But what kept me going was knowing how much simpler and more effective analytics could be if we got it right.

## Lessons Learned Along the Way
One thing I’ve learned through this process is that solving big problems often means challenging assumptions. For years, businesses accepted that duplicating their data into third-party tools was just “how it’s done.” But when you step back and question why things are done a certain way, you see opportunities for change.
Another lesson has been the importance of listening—to customers and to partners like CDPs. Every feature we’ve built at Mitzu.io has been shaped by real-world feedback from people who are just as frustrated by traditional analytics as I was.

## The Road Ahead
Mitzu.io is still young, but our impact already feels significant. Companies like Prezi, Khatabook, and Shapr3D are using our platform to simplify their data stacks.
For me, this journey isn’t just about building a successful product—it’s about fixing something that’s been broken for too long. It’s about allowing businesses to analyze their data without all the unnecessary complexity and cost.