Automating Trust in Cloud Data Migration

End-to-end validation, workflows and AI-assisted conversion for migration at scale

By: Dmitriy Kontarev, Data Product Director, Chase

• Chase is migrating its analytical and reporting data, pipelines, and business logic from legacy on-premises systems to a modern cloud data platform.
• To manage the scale and complexity of this migration at an accelerated pace — and to ensure we can support future modernization efforts — we focused on automating every step to build confidence and speed.
• This approach led to the development of a real-time data validation platform that delivers trust, transparency, and continuous readiness for both current and future needs across our Consumer and Community Banking (Chase) enterprise.

Together with a talented team and technology partners across Chase, we built a real-time data validation platform to automate validation, workflow and cutover control end to end. Designed to streamline complex, high-stakes migrations, it now delivers a repeatable process with clear standards, accountable approvals and real-time visibility — enabling teams to move at pace without compromising trust.

The Challenge: What and Why

At Chase, we’re executing large migrations that span hundreds of thousands of data objects, millions of fields, thousands of end users, documented reports and workflows, and hundreds of applications.

The goal: modernize our data estate for scalability, compliance, and new capabilities, while ensuring business continuity and trust in every cutover. We are also preparing for a future where agentic, AI-ready use cases — such as automated data quality monitoring, self-healing pipelines, and AI-driven analytics — will require even higher standards of data integrity, traceability and automation.

At this scale, even small discrepancies — such as a trailing space, a hidden character, or a null vs. empty string — can be the difference between a model that works and one that fails. We needed more than a one-time, narrowly focused solution; we needed a platform that delivers trust, transparency and end-to-end control.

How We Solved It: Real-Time Data Validation Platform

The Real-Time Data Validation Platform we built meets that need — a suite for data validation and controlled cutover.

Cloud migration at Chase is about transforming how we operate, innovate and serve clients while keeping precision and reliability non-negotiable. Our journey began by establishing a firm Definition of Done (DoD) with our users — clear standards for conversion, validation, workflow and auditability — which now guide the ongoing migration. The platform provides a common, user centric process that meets those needs across risk-aware domains without compromise.

Step by Step: The Platform’s Role in the Migration

Our approach is methodical and user centric. We start with users and their queries. The platform enables users and application owners to convert and validate SQL from the legacy on prem system to the target cloud data system via two paths: self-serve (paste to convert) and proactive (we pre-convert, validate and stage known queries so teams are ready when they choose to migrate). The platform then runs each query in both environments and verifies exact matches on partition counts, values and schemas. For edge cases, our large language model (LLM) assistant — working alongside the rule-based engine — lifts conversion success toward the 99%+ mark.

As we migrate data assets, pipelines and business-as-usual (BAU) processes, complexity grows. Entire datasets — each with its own structures, histories and business logic — are recoded for the cloud, transforming legacy assets into cloud-ready, governed resources. The platform underpins this phase by testing against the DoD, automatically documenting changes while allowing teams to add clarifying notes, and coordinating workflows end-to-end, including user acceptance testing (UAT) and line of business (LOB) reviews with full audit trails. Leadership has real-time visibility into the status of every asset, the progress of each migration wave, and a live burndown of remaining work. When assets are ready, the platform coordinates cutover from validated to production, with approvals and notifications handled in flow.

Quantifiable Impact and User-Centric Automation

The platform’s impact is measurable. We have enabled analysts to migrate to the cloud roughly four months sooner, saved tens of thousands of total hours of manual effort, and certified thousands of data objects for use. With thousands of monthly active users, we maintain a strong net promoter score (NPS), reflecting user satisfaction. To date, the platform has supported hundreds of thousands of unique query conversions and compared tens of thousands of data objects, streamlining onboarding and reducing technical debt. These automation capabilities are built for users, removing manual effort, reducing risk and accelerating time-to-value.

AI and LLM: Raising the Bar for Automation

Innovation is central to the platform. Assisted conversion combines a rule-based engine with an LLM-powered capability to reach 99%+ query conversion rates. In the platform’s workflow module, a built in LLM summary feature helps users save time by summarizing validation results, surfacing key insights and preparing end-user notes — accelerating reviews and approvals. LLM features are gated by PII and PCI safeguards and human-in-the-loop validation to maintain controls and trust.

A Platform for Everyone

The platform is used by thousands across the business: data delivery and engineering teams; analysts; data scientists; project managers; data owners; and business users. Its all-encompassing capabilities — change management, workflow coordination, automated testing, dashboards, and reporting — make it the central nervous system of our migration effort.

A Mark of Trust

Within Chase, when an asset carries the platform’s certification, it means the data has been rigorously tested, validated and certified. Leadership, stakeholders and end users can move forward with confidence, knowing the migration was done right.

What You Can Do: Lessons for Other Organizations

If you are planning or in the midst of a large-scale data migration, here are a few lessons from our journey:

• Build a zero-tolerance validation process that leaves no room for silent data drift.
• Treat migration as a product, not a one-time project, with clear ownership and ongoing accountability.
• Create a chain of accountable stakeholders and enforce a clear DoD for every migration step — establish the DoD ahead of time, ensuring all stakeholders are aligned.
• Establish a comprehensive migration inventory and use it as your foundation for planning and tracking.
• Automate validation, approvals, and reporting to accelerate migration and minimize human error.

Looking Ahead

As we continue our journey to the cloud, the Real-Time Data Validation Platform remains at the heart of our strategy, driving speed, efficiency and trust. Our vision is for the platform to become the tool of choice for data reconciliation and migration across JPMorganChase, setting a new standard for enterprise data management.

Like what you’re reading? Learn more about how we work across product, experience and technology by subscribing here.

JPMorgan Chase is an Equal Opportunity Employer, including Disability/Veterans

For Informational/Educational Purposes Only: The opinions expressed in this article may differ from other employees and departments of JPMorgan Chase & Co. Opinions and strategies described may not be appropriate for everyone and are not intended as specific advice/recommendation for any individual. You should carefully consider your needs and objectives before making any decisions and consult the appropriate professional(s). Outlooks and past performance are not guarantees of future results.

• • Any mentions of third-party trademarks, brand names, products and services are for referential purposes only and any mention thereof is not meant to imply any sponsorship, endorsement, or affiliation.