Constant, widespread technological evolutions tend to distract businesses in pursuit of the next big ROI-driver. However, some traditional processes, if neglected, will lead to foundational failure that impact those shiny innovations downstream. ETL solutions, for example, continue to play a crucial role in effectively managing data for today’s latest innovations.
ETL Evolution: Why It Is As Mission-Critical As Ever in the AI-Era, DBTA’s most recent webinar, featured John O'Brien, principal advisor and industry analyst, Radiant Advisors, and Abhilash Mula, senior manager, product management, Informatica, who examined the mission-critical role of ETL in the AI era, as well as how to future-proof data strategies in an ever-shifting landscape.
To begin with, O’Brien highlighted the follow as the top ETL-related challenges facing companies in 2025:
- Data engineering for modern data platforms
- Must deliver data products faster
- Improve data management to unlock generative AI (GenAI) and agentic AI
“In order to have better data management, you need better data engineering with ETL,” O’Brien noted. And, with a lack of a defined data and AI strategy and architecture roadmap being one of the top obstacles for enterprises with cloud migration—according to Radiant’s 2025 Market Survey—seriously examining enterprise ETL will play a significant role for business success, especially in regard to AI.
Echoing O’Brien, Mula added that, because of enterprise shifts relating to AI, automation, and massive cloud migrations, “getting the right data to the right place at the right time is more challenging and essential than ever.”
Yet, the complexity of modern data and applications has significantly increased data silos and fragmentation, halting effective data management and access. In the AI era, models depend on clean, fresh, accessible data—where advanced data engineering becomes absolutely mission critical, according to Mula.
Informatica’s Intelligent Data Management Cloud (IDMC) provides the proper foundation for both traditional ETL and advanced data engineering as a “unified, end-to-end platform that covers your entire data journey from integration to governance to AI-readiness,” said Mula. “At its core, IDMC delivers powerful data integration,” including scalable cloud data integration and application integration that can connect to business systems.
With IDMC’s cloud data integration services, customers can expect:
- 335% average ROI
- 67% faster data processing
- 90% faster connector development
- $3.9M average annual benefit
- 30% improved developer productivity
- 37% shortened pipeline development
- 3 months average payback
This is only a snippet of the full ETL Evolution: Why It Is As Mission-Critical As Ever in the AI-Era webinar. For the full webinar, featuring more detailed explanations, a Q&A, and more, you can view an archived version of the webinar here.