ETL and the Ice Axe: What Data Engineering Has in Common with Mountaineering

Building a modern data warehouse increasingly resembles a well-planned mountaineering expedition. We can try to reach the summit with minimal gear — as the pioneering climbers of old did — or we can take advantage of modern tools that make the journey safer, faster, and more predictable. In the world of data, one such tool is Coalesce.

A Data Warehouse Is Like Mountaineering

Think back to the early days of climbing. Equipment was minimal — ropes were often made of hemp, and belaying relied on basic techniques like the clove hitch. Climbers depended primarily on their own skill and experience. It was possible, but it demanded enormous caution and deep expertise.

That is exactly what a traditional ETL process built entirely by hand looks like. Every element — from transformations to table dependencies — has to be designed and maintained manually.

Modern climbing looks completely different. Ropes are synthetic and far stronger. Belay devices have assisted-braking mechanisms. Equipment is manufactured from advanced materials that are simultaneously lightweight and highly durable. There are even special belay glasses that let a belayer look up at the climber without straining their neck — a small piece of gear that dramatically improves comfort on the job.

None of this makes climbing trivial. It still requires skill, planning, and experience. But it does make the activity safer, more efficient, and accessible to a larger number of people.

Coalesce works the same way in the world of data. It does not replace the data engineer, but it provides tools that significantly ease the work and reduce the risk of errors.

What Is Coalesce?

Coalesce is a platform for designing and managing data transformations. It operates as a layer on top of analytical environments — particularly popular on the Snowflake platform. It enables you to build ETL processes and data transformations visually, using a dependency graph between data objects, rather than relying solely on hand-written code.

In practice, this means that instead of writing hundreds of SQL scripts and managing their execution order, you design the data flow structure inside the tool, which automatically generates code and controls the dependencies between tables.

Why Do We Even Need a Low-Code ETL Tool?

At first glance, it might seem that since data transformations can be written in SQL, an additional tool is unnecessary. And it’s true — a single transformation can be written relatively quickly. The problem only arises once the system starts to grow.

Modern data warehouses often consist of hundreds of tables, multiple transformation layers, and a complex web of dependencies. Every change in one part of the system can affect many other elements. If everything is stored purely in code, maintaining such an environment begins to resemble managing a vast collection of interrelated scripts.

Tools like Coalesce were created precisely to reduce this complexity. Instead of writing similar code from scratch each time, you can use ready-made transformation patterns, visually manage table dependencies, and let the system automatically generate a large portion of the code. This shifts the data engineer’s work from “writing infrastructure” to designing data logic.

Can You Build ETL in Snowflake or Microsoft Fabric Without Coalesce?

Absolutely! Both Snowflake and Microsoft Fabric are complete analytical platforms that allow you to build ETL processes without any additional tools. In Snowflake, transformations can be based on SQL, Tasks, Streams, or orchestration tools such as Airflow or dbt. Microsoft Fabric, in turn, offers Data Factory pipelines, Spark notebooks, SQL transformations, and dataflows.

All of these solutions allow you to create a fully functional data warehouse. Coalesce is therefore not a mandatory component. It is a tool that simplifies how you work with the platform and helps manage transformations in a more structured way.

What Advantage Does Coalesce Offer?

The biggest difference appears when the system becomes truly large. At that point, the challenge is no longer writing a single transformation — it’s managing the entire data architecture.

Coalesce brings structure and visibility to the process of building a data warehouse. Dependencies between tables are presented as a graph, making it easy to see where data comes from and which elements of the system are connected. Transformations can be built faster, because many repetitive elements are generated automatically. Teams working on the project share the same patterns, which reduces code chaos and makes the system easier to maintain over the long term.

Most importantly, the tool lets you focus on business logic rather than on the technical details of implementation.

To sum up: ETL can be built without Coalesce, just as you can climb with minimal gear. Platforms like Snowflake or Microsoft Fabric provide all the basic components needed to work with data.

However, in large projects, productivity, transparency, and system maintainability become critical. Tools like Coalesce help manage the growing complexity of data environments, automate repetitive parts of the work, and allow teams to focus on what truly matters — building value from data.

And in the world of data — just as in the mountains — having the right gear often determines whether the journey will be a struggle for survival or a well-planned and safe ascent.

Phronesis Path is SQL Day 2026 Gold Partner – See Coalesce live in Wrocław 11th – 13th May 2026