At DataTools Pro, we are longtime users of Alteryx and have termed it the ultimate data Swiss-Army knife. Having to replace Alteryx for enterprises is not an easy decision because skilled Alteryx builders are wildly productive turning data into information.
The power of Alteryx is the ability to rapidly transform and validate disparate data without writing code. This pattern remains ideal for analysts who struggle to automate complex data workflows in Excel. Data engineers who would typically write code to transform data sometimes lack business context and experience understanding acceptable validation rules. The symbiotic rise of Tableau allowed Alteryx as a high quality “ETL for Analysts” solution thrived.
Alteryx Rocketship : The State of Data in 2010-2020
- Data management and business intelligence were centralized but moving toward self service
- Analytics turn times were measured in quarters and years
- Data and BI teams were severely backlogged and unable to meet demand
- Data was spread across windows file shares and on premise databases
- Large enterprise data warehouses were extremely slow to develop
- The rise of self service visualization with Tableau created the perfect symbiotic relationship
No-Code can get in the way of efficiency
A few years ago, while using Alteryx with Snowflake, I found myself leaning on the Alteryx Python tool to handle extreme edge cases where 10-15 nodes could be expressed in a few lines of code. For example, a rolling 60 business day (minus bank holiday) window function is something we created as a UDF in Snowflake.
Shift from ETL to ELT
As a head of data and analytics and now as a consultant using Snowflake has been a game changer. As an enabling technology, it has democratized the data warehouse the same way Alteryx did for no code ETL 15+ years ago. Now, I can pump millions or hundreds of millions of rows into Snowflake with low storage costs, process, and then deliver to any analytics tool securely.
There are many new drag and drop, flow based solution that have learned and improved on the ETL tools that came before. When it comes to analytics-focused data flows for Snowflake, Datameer has long been my choice after discovering them looking for a low code solution to handle the transformation layer.
Demystifying Alteryx Flows like Messy Code
A SQL engineer can solve problems with un-optimized, difficult to follow code. Similarly an Alteryx builder can create overly complex flows, or worse stitch many flows together that can take days to decouple. In 2025, I can take tens of thousands of lines of SQL code, pump it into ChatGPT and immediately demystify, document and understand what to do next. An Alteryx installation that has grown over time naturally accumulates technical debt.
To demystify Alteryx, there are numerous tools that we use to inventory and understand Alteryx Flows.
Why Replace Alteryx with Snowflake Powered Data, Analytics and AI
Cost, complexity and operational risk are the three consistent themes we see for clients looking for alternatives to Alteryx. There are numerous tools in the market for no-code flows that have advanced beyond Alteryx. We are happy to introduce you to them.
If your enterprise’s data strategy calls for using Snowflake as the core data platform for analytics and AI, we highly recommend Datameer!
We are here to help you inventory and plan your migration
DataTools Spotlight: Datameer is our Snowflake Tool of Choice
For this month’s DataTools spotlight, I wanted to share my long time favorite for Snowflake tool, Datameer. Years ago, I found Datameer solved my slow Snowflake adoption problem. My team was loaded with requirements but had only one data engineer on staff. Historically we used Alteryx and Tableau prep to get by. Extracting data from…
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