"A black box." 

"Creates spaghetti code." 

"Great for small shops, but not for enterprises with serious security and governance needs." 

These aren't random complaints – they're the voices of data professionals looking to move from Alteryx in today's cloud-centric world. As the CEO and Co-Founder of Prophecy, I've heard these concerns in conversations with industry leaders and data teams alike.

If you're considering this move, you're not alone. I'm here to guide you through your options.

Still a game-changer?

When Alteryx first hit the scene, it was a game-changer. Business users and data analysts finally had a tool that could liberate them from the shackles of spreadsheets and manual data wrangling. 

But times have rapidly changed in the world of data. Data teams are now looking for solutions that are modern. They want the governance, scalability, and cost-effectiveness that comes with a cloud-native architecture. 

With business logic trapped in proprietary workflows, teams are also looking for a solution that easily migrates and doesn’t leave them feeling trapped. 

As one witty customer put it,

"I've been divorced twice, so I love that your open-source code doesn't lock me in." 

Charting a new path

As you contemplate your next steps, let's explore the options available for moving beyond Alteryx.

Option 1: Stay the course

It’s tempting to stay the course with Alteryx. With existing users and embedded workflows, it's the path of least resistance.

However, as a forward-thinking leader, it's crucial to consider how the data landscape has evolved. The question you need to ask yourself is: can your organization afford to lag behind as the industry moves towards more scalable, secure, and flexible cloud-native solutions?

Organizations are now looking for solutions that are:

1. Modern. Running natively on your data cloud platform, intelligent with integrated generative AI, and cost-effective with no duplicate governance and operations.
2. Built for production. With well-governed pipelines that leverage data cloud governance and security like Databricks Unity Catalog, scale and run across the entire data set, and move from ad-hoc to production using git with standard change management and orchestration.
3. Easy to migrate. Able to automate migration, delivering open source code with no lock-in, and supporting end users with a familiar visual interface.

It’s clear that the future of data preparation is increasingly cloud-centric and open-source code friendly.

Option 2: Dive into SQL code for transformations

Transitioning to code-based transformations is another option. This approach offers enhanced control over data transformations and often improves performance, especially for large-scale operations. It also aligns data work with software development practices, enabling version control and continuous integration.

However, this path comes with its own set of challenges. Teams accustomed to visual interfaces may face a steep learning curve, and organizations might find themselves more reliant on specialized data engineering skills. While SQL is relatively accessible, SQL for multi-step data transformation is far more complex than for data lookup and complex data preparation processes can become difficult to manage and maintain over time.

Ultimately, the shift to code-only transformations can enhance data preparation, but the drawbacks are significant - making this option a non-starter for most organizations.

Option 3: Embrace the future with Prophecy

At Prophecy, we've taken a different approach to address the challenges faced by organizations moving beyond Alteryx. We've built the Data Transformation Copilot, combining the intuitive interface that business users love with the intelligence of AI and the power of code, running natively on your cloud data platform.

Our solution offers both visual and code interfaces all powered by genAI technology. This dual-interface approach enables all users - from data analysts to data engineers - and makes them more productive.

We've built the Copilot to integrate seamlessly with cloud data platforms like Databricks, ensuring strong governance, no costly rewrites, and eliminating the management overhead that comes with having to manage two systems. Our native integration also eliminates many of the scaling issues that plague traditional tools.

With Prophecy, visual pipelines are turned into standard, open formats, ensuring users are never locked in - overcoming a key challenge of legacy ETL and other visual data preparation tools. We've also made our platform extensible, allowing for the development of standards and frameworks via plugins, which business users can then leverage.

This combination of intelligence, modern cloud integration, and openness positions Prophecy as a forward-thinking solution for organizations looking to move beyond traditional data preparation tools. It's designed to meet the evolving needs of data teams in today's cloud-centric, AI-driven landscape.

Make the leap with Prophecy Migration Copilot

Change can be daunting, especially when you have years of workflows built in Alteryx. That's why we've developed the Prophecy Migration Copilot. This tool automates the migration of Alteryx workflows to Prophecy, turning what could be a weeks-long process into a matter of minutes.

A solution provider to major health insurance providers was looking to modernize data preparation to better leverage Databricks while maintaining an intuitive visual interface. However, they also needed to move their existing Alteryx workflows. The team was able to use Prophecy Migration Copilot to transition 80+ workflows and complete the move off Alteryx in just 10 weeks. They can now fully leverage Databricks to process data in minutes compared to hours and use Prophecy to provide a familiar interface to their data teams. The result? A more scalable, governable, and cost-effective data preparation process.

The Road Ahead

If you're considering a move away from Alteryx, I invite you to explore what Prophecy has to offer. We'd love to show you how our solution can help your organization navigate this transition and emerge stronger on the other side.

After all, in the world of data, those who adapt don't just survive – they thrive. Are you ready to take the leap?