Good morning everyone. I'm Nina Villa. I'm a program manager at three Code Solution. Today I will walk you through on how Enterprise can drive successful large scale migration using the process automation and AI innovation. So over the next few minutes, we will explore how automation transform migration from one-time project into a continuous capabilities that fuel digital transformations. I. So first we will see the evolution of enterprise migration. In the past, migrations were simple lift and shift activities, just moving the workloads from one place to another. Today, they have become far more complex involving multiple teams, tools, and compliance framework. But the future is different. It is about treating the migration as a strategical capacity, so continuous automated transitions where system evolved dynamically without disrupting the business operations. So in today's world, automation is no longer an optional. It is a strategical necessity for any organization. So with respect to migration, manual migration comes with a real pain points, long project timeline, unpredictable result, and a high risk of errors. So automation directly addresses these issues by shortening the delivery timelines, improving the predictability. Enhancing the data quality and freezing the specialized team for innovation instead of repetitive migration work. So automation is not just about speed, it's about reliability, consistency, and governance. Now we will see how migration can be done in a scalable and a repeatable way. So each organization should anchor them around the below four pillars. Number one, discovery automation. Number two is a transformation engine three is the orchestration platform, and number four is the automated testing. So each pillars complement the other together. They ensure every step from analysis to execution is efficient and auditable. So now we will move on with the first step, which is nothing but the discovery automation here. The process will automatically discover all the dependencies. Data lineages and also the system interconnection. So in traditional method, documenting this relationship to take weeks or months. Now with this automated discovery, we can visualize the entire ecosystem, understand how every data source and the services impact each other, and allowing the team to plan the migration intelligently. So once we know what to migrate, automation help us to handle the transformation at scale. This includes automated schema, conversion code, refactoring, and bulk data migration. For instance, tools can now convert the Oracle schema to Postgres, SQL rewrites store procedures, and migrate the terabytes of data with built-in validation. The goal is accuracy, speed, and minimal manual touch points. So here we see the three most common migration pattern. Number one is the cloud migration, like moving the workloads to AWS Azure or GCP. The second one is the big data modernization, like transitioning from Hadoop to modern cloud platform. And third one is the data warehouse evolution modernizing to a platform like Snowflake. With automated schemas and query translation. So each pattern benefits largely from automation, reducing the cost and time while improving the confidence. So now we move on with the intelligent orchestration. So even with automation, orchestration is critical, like how we sequence and monitor every step. So intelligent orchestration defines workflows. Executes them automatically adapts to condition in real time and validate each stage continuously. It's like having an air traffic controller ensuring every migration activity runs smoothly without collision or downtime. So now we have come to the last pillar, which is nothing but the automation testing. So automation testing ensures quality and reliability across every stages of migration. It systematically validates each component against the functional and the performance benchmark, achieving a coverage that manual testing can't even match. So differential testing automatically the source and the target systems to catch the hidden logic or any data issues early with real-time monitoring and automated rollback. Teams gain instant visibility and can recover rapidly if problem arise. So making migration faster, safer, and far more predictable is the main goal for this automation testing. So now we are moving towards how AI had exponential values to these migrations. So mission learnings can analyze previous migrations to predict effort, cost, and risk. And then the AI driven automation process are just workflows dynamically to resolve issues in real time. And then the last one is the predictive analytics. Forecasting the potential bottlenecks before they happens. So these things allow the team to act proactively rather than reactive. So zero time migration strategies plays a key role in all the organizations. Business continuity is non-negotiable. So modern strategies like continuous replication, intelligent routing, and instant rollback allows us to migrate system without user even noticing. This means that no weekend cut over, no loss, productivity, and all migration happens while the business keep running. So the ultimate goal is to move beyond project-based thinking and to make migration and enterprise capability. That means investing in automation platform, nourishing skilled teams, building repeatable frameworks, and making a solid technology foundation enterprise that do this can adapt quickly to new technology and gain a competitive edge through an agility and speed. So here is a simple roadmap to start. Assess your current migration process. Define your target automation vision, then implement gradually beginning with the high impact use cases. Then measure and optimize continuously. It's about building momentum. Start small, learn, and then expand every success compounds into a long-term transformation. Thank you all for joining. I hope the session gave you a new perspective on how automation and AI are redefining the enterprise migration. So let's go and explore how we can create more migration excellence within our organizations. Thank you.