5 Takeaways from Snowflake Summit 2025 That Shape the Future of Business
Why Snowflake Summit 2025 Signals a Turning Point for Process Mining I just returned from Snowflake Summit 2025, and it’s clear: we’re entering a new era of...
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In the shifting landscape of enterprise technology, a quiet revolution is underway — one that reshapes how businesses understand and optimize their operations. The revolution is process mining. But not as it’s been practiced in the past.
For years, organizations accepted a paradox: to understand how their processes run, they had to move, duplicate, and transform data — often into proprietary formats, pipelines, and cloud stacks. This meant building massive data integrations, maintaining fragile ETL chains, and locking themselves into vendors that controlled not only the tooling, but the data model itself.
This old approach is no longer viable.
The future of process intelligence belongs to platforms that work where the data lives — not those that extract and replicate it elsewhere.
At its core, process mining reveals how work actually happens. It traces digital footprints through systems like SAP, Salesforce, or Oracle to reconstruct business processes end-to-end. Done right, it surfaces inefficiencies, variants, bottlenecks, and automation opportunities.
But here's the catch: most legacy process mining tools require you to move data from your operational systems into their proprietary cloud. That means:
In some implementations, over 80% of the total effort and cost went not into the analysis — but into the plumbing: mapping fields, writing SQL scripts, staging data, and reshaping event logs to fit a rigid model.
This is the opposite of agile intelligence. It’s static, brittle, and expensive.
Now contrast this with a modern approach: process mining that runs natively inside your existing enterprise data cloud.
If your business runs on Snowflake, for example, your process mining platform should query that data directly — with no duplication, no movement, no reshaping. This isn’t just a technical preference; it’s a strategic imperative.
When process intelligence runs inside your data cloud:
This is what process mining should look like in 2025.
Most enterprises don’t realize they’re walking into vendor lock-in until it’s too late. What begins as a promising proof of concept ends with enterprise-wide data pipelines feeding a single vendor’s cloud — making future migration nearly impossible without starting from scratch.
Here’s what to look out for:
It’s not just about the cost — it’s about the loss of flexibility. Once your data is modeled, transformed, and hosted in someone else’s architecture, the cost of change becomes prohibitive. Process intelligence becomes a silo, rather than a strategic layer across the enterprise.
The most forward-thinking process mining platforms don’t just show you what’s wrong — they simulate what would happen if you fixed it. They let you model outcomes, forecast ROI, and guide automation. But simulation is only as good as the data it uses.
That’s why native access to real-time enterprise data matters. You can’t simulate a future process using stale, extracted snapshots. You need live, governed data. And you need it now.
The same goes for AI. Generative and predictive models must be trained on clean, complete, and current process data. That only happens if process mining tools work within your existing data cloud — not outside it.
CIOs and data leaders have a choice: keep building parallel data ecosystems to serve a narrow slice of process analytics — or embed process intelligence natively into the enterprise data architecture.
The latter approach:
Process mining is no longer a standalone tool. It’s an enterprise capability. And like all strategic capabilities, it must live where the enterprise lives — inside your data cloud, not outside it.
Business leaders no longer accept data silos, black-box models, or technology that serves the vendor more than the customer. Process mining is too important to be locked away in proprietary clouds.
If you want speed, flexibility, and insight you can trust — keep your data where it belongs.
Where it lives.
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