Sample Blog

Using AI for legacy data modernization? Don’t fall into this trap

Next Pathway — Thu, 14 May 2026 04:00:00 GMT

Five Reasons why Next Pathway is Better than a Box of Consultants for Legacy Data Migration

Next Pathway — Mon, 27 Apr 2026 04:00:00 GMT

Modernizing Legacy Stored Procedures: An Automated Path from Oracle PL/SQL and SQL Server T-SQL to Snowflake Snowpark

ovorobey@nextpathway.com (Next Pathway) — Fri, 24 Apr 2026 04:45:00 GMT

Legacy ETL systems are holding back AI initiatives. Learn the warning signs that indicate it's time to migrate to Snowflake.

The Unified ETL Modernization Blueprint: Consolidating Informatica, DataStage, and SSIS Environments on Snowflake

ovorobey@nextpathway.com (Next Pathway) — Fri, 10 Apr 2026 04:30:00 GMT

The Agentic Gap: Why Your AI Strategy Is Stalling In The Legacy Warehouse

cmathur@nextpathway.com (Chetan Mathur) — Tue, 31 Mar 2026 04:45:00 GMT

Time-to-Snowflake: Why Speed Matters More Than Ever In The AI Era

cmathur@nextpathway.com (Chetan Mathur) — Thu, 26 Mar 2026 04:00:00 GMT

We are living through a unique moment in industrial history. The global shift toward AI is creating unprecedented demand for modern data infrastructure and the enterprises that modernize fastest will set the pace for everyone else. In this environment, time-to-Snowflake is a strategic competitive advantage.

Accelerating the AI Data Cloud: The Automated On-Ramp for the New Industrial Era

cmathur@nextpathway.com (Chetan Mathur) — Wed, 25 Mar 2026 04:00:00 GMT

At GTC 2026, the global enterprise timeline was reset. We are entering the largest infrastructure buildout in history, a reinvention of the data center designed to manufacture intelligence. For enterprises, there is a hard truth between AI ambition and actual results because infrastructure without readiness is just expensive overhead.

Designing the four pillars of AI readiness: Data platforms, pipelines, compute and governance

Clara Angotti — Tue, 24 Mar 2026 04:00:00 GMT

Modernizing an enterprise is an architectural challenge that cannot be solved by simply layering new technology over old foundations. While the industry is fixated on the intelligence of AI models, the actual value of those models is dictated by the infrastructure beneath them. To move beyond experimentation, leaders must design four specific pillars of readiness that ensure data is fluid, documented and accessible to modern, autonomous workloads.

The $1 Trillion Infrastructure Cycle: Why AI Factories Stall At The Legacy Gate

ovorobey@nextpathway.com (Next Pathway) — Sat, 21 Mar 2026 04:30:00 GMT

The Teradata Modernization Framework: Transitioning Legacy Infrastructure to the Snowflake AI Data Cloud

cmathur@nextpathway.com (Chetan Mathur) — Tue, 24 Feb 2026 05:00:00 GMT

For decades, Teradata was the undisputed foundation of the enterprise data warehouse. However, the legacy constraints of on-premises hardware and rigid scaling models have made it an obstacle to AI-driven innovation. While the move to the Snowflake AI Data Cloud is the clear strategic path, the volume of proprietary Teradata BTEQ scripts, stored procedures, and complex macros often creates a significant migration deficit.