Hey. Hi. This is, I like process of experience into the data housing such as SSIS tool Informatica Under, and also having experience in the reporting tools such as SRS Pyramid reporting. Today I'm going to be, discuss our, the serverless revolution, how the cloud-based shared data integration is transforming the enterprise data management. Cloud-based data integration has image as a transformative force in enterprise data management revolutionized how our nation handles the exceptional growth of our data across the separate sources. With a global data creation projected to reach 1 75 gtz by 2025, companies now struggle with integrating data from an average of full disparate sources. Organization implementing cloud integration solutions reported 30 to 40% direction in the total cost of ownership and up to 60%. Four. So inside competitor traditional methods, unlike convention on the six solutions, requiring eight to 12 months of deployment. Cloud integration for deployment times, averaging just six to eight weeks while providing significant uptime improvements. Let me go to the slide. So the paradigm shift in enterprise data management, we have a traditional integration on the cloud. Integrations on-prem solutions dominated 80 by 88% of the entire enterprise integration market in 2010 declining to the approximately that 5% by 2022. The systems present a significant limitations with over 70% of organization reporting scalability, constraints and integration phase during the peak periods. And coming to the cloud integration, if you see here, like the cloud platform supported workload variations of 2200, 300% with the without a performance integration, organizations nowadays, organizations are opting cloud integration reports 70% direction in their primary times, and 85% decrease in net related incidents with the subsequent growth projected and when coming to the cost benefits of the cloud integration, if we see here on the chart, like we have the cost category on traditional integrations. And the cloud integration on the directions. If you see the the interest cost, traditional integrations is a hundred percent. And when it comes to the cloud integration, it's 55.6 50 to 65, and reduction is 35 point 35 to 45. And coming to the maintenance in the duration integration, it's 20 to 25. And the cloud integration, it's some to 10 and reductions is 62, 65. When come into the development that in duration integration, it's a hundred percent. Cloud integration for 2 2 16 and ion is 40 to 50. And total cost of the ownership it's traditional is a hundred, and the cloud integration is 60 to 70, and election is 30 to 40. Come, let's move to the initial slide. So if you see here this this are the evolution of the data integration technologies. So the first one is the traditional ETL error. So manually will process request an average of 40 percent of 40 develop per hours for integration on premises. Solution dominated 80% on integration market in 2010. So when coming to the second point, it's a transition period. And the third point is the cloud native integration. And the fourth one is the feature productions like back 1 25 or 80% of the operation will add up to the clause based integration platform as a primary integration strategy. Okay, so let me show the chart here. If you look into the chart here, the enterprise application education market growth. So if you look at like 2022, it's 25% and like 2024, it's like more than near two 35% down 20, 26, et cetera have grown to around 40%. Year two and 2028, it's going to be between 50% and 2030. Expectations is like around like more than 65 plus. So let's move to the next slide. Like if, here in the next slide we have the leading cloud integration platforms. So we have a different cloud integration platforms such as a WS Q and the Microsoft Azure Data Factory and the Google Cloud data of a data flow. This platform collectively control over 70% of authentication platforms. Are they continuity, evolving rapidly with the numerous features releasing, including emission learning based data. Quality monitoring on the automated all edge tracking. So let me move on to the next steps slide. So if you move to the next slide, like here, like we have the customer satisfaction with the cloud integration platforms. It see the a Ws view like it's 4.5 or the five on the other data factories 4.3 and the Google cloud data flow is 4.4. So let me move on to the next slide. So if you come to the next slide, like here we have several less architectures. The new para, if you see the diagram we have a automatics scaling. So which hand the launch volume regions and within the second cost optimization development focus management. And let me move on to the next slide. If you see here, like we do have like even driven integration benefits. If you see here even reduction means triggers based on the data changes or schedule events on the automated process. Authentication workflows without the manual intervention and coming to the real time analytics enables data. Yeah, insights from the process. Data and data ion upgrades flow through the head pipeline within the minutes. Let me move on to the next slide. So if you see here, like in the slide, like we have the financial services sector implementations. What are the integration challenges on the cloud solution? Challenges on them results achieved. So this case demonstrates the transformation potential of cloud integration in a highly regulated environments. The majority of the financial institutions implementing similar solutions report enhanced analytical capabilities with the dramatically link decreased time to insight compared to the previous premises systems. If you see, if you go to the next slide, like we have healthcare sector implementations. So the initial integration challenges for the healthcare ethical sector and the cloud integration approach, what they follow and what are the transformation achieve in this particular healthcare sector on the ongoing benefits. As a Highland reports, more than 80% of healthcare products are implemented, some type of the cloud service, such as applications, infrastructure, or deferred from services enabling sustainable improvements in both operational efficiency and quality of care. Let me move on to the next slide. We do have the manufacturing sector implementations, I water data collections and cloud integration, predictive analytics, and the operational improvements. So like the multinational manufacturing corporate implemented cloud based integrations to transform their operations through comprehensive data collection analysis. Let me move to the next slide. We have the implementation success factors, like the first one is the phase migration approach. And the second one is the hybrid architecture during the transitions. And the third one is the designed data governance and the executive sponsorship and the common success pattern emerge from the cloud. Integration across industries, organizations that follow the best practice of consistently achieve better outcomes with the fewer implementation challenges. Let me move on to the next slide. Like the feature of the enterprise data management. So if you see here, like AI integration, machine learning algorithms, which increase the automated data mapping transformations and the quality management reducing manual effort while improve the accuracy and duty change the data structures. N let me move on to the next slide. Multi-cloud integrations. Organizations will increasingly adopt to the integration statuses that span multiple cloud products. Last one is the real time, everything. The ship, they the ship toward the real time data process and will accelerate for the batch. Interesting approaches increasing, replaced by the streaming architectures that enables ate insights and action based on current data. To conclude like the cloud-based data integrations represents a fundamental transformation in. How enterprise managers process and the value of from their data assets. As this technology continue to evolve, they will increasingly become the foundation upon the nation, build their data strategies, enabling them to harness the full potential of their information as increasingly data driven business landscape. That's all about it. If you have questions you can ping me in the LinkedIn or like you can reach me at Gmail. Gmail.com. Thanks for giving me this opportunity.