Digital transformation is the agenda of many companies across the globe that own differentiated legacy IT. Companies are using cloud based applications or moving their applications to cloud for getting the edge in a digital world. As a result, companies are creating a hybrid ecosystems where the data is siloed between cloud and onpremise systems. Because of this great divide nearly half of the companies are failing to connect their systems, onboard data and exchange it with their partners. The results are suboptimal utilization of resources and increased total cost of ownership (TCO). For upstream development and get benefits downstream, organizations should adapt an onboarding software and surmount the integration challenges. There are innumerable benefits of onboarding customer data with an automation tool. It delivers unprecedented agility, scalability, and interoperatbility to create connections in simple steps. Without automation organizations need to deploy a lot of Java developers for handcoding computer to computer connectivity. Heavy coding onloads heavy burden on IT team and derails from their core competency. Reallocating staff reduces time to market of IT professionals. Automation helps Teams to accelerate time to revenue and drive top line profitability. Complexity grows when an organization deploys next generation applications to meet the requirement of entities, i.e., partners, customers, stakeholders, etc. The network is obstructed when there is lack of standerdization between business systems. Companies fail to get a single view of applications and traffic problems spike. Point to point connection between these systems become fatal in the long run as they create a complex hairball of coding that is not scalable. Network downtime heavily impacts business outcomes and profitability. This problem can be surmounted with the help of a onboarding software that balances load during network spikes. Automation of customer data onboarding delivers reusable connectivity to handle network spikes and develop connetcions faster. It injects a greater degree of interoperatability in teams to handle spikes effieciently. Any digital initiative will fail if there is no foundational support to the DNA of digital technologies. To ensure fondational support, organizations should have triggers in place for improving data governance. Better data governance inreturn ensures that quality data is being with shared with stakeholders. Quality data can be pushed into Big Data technologies for analytics purposes. Integration from a centralized platform also helps in analyzing network and latency issues and fixing the gaps in minimum period of time. With better monitoring, organizations can troubleshoot technicalities and avoid gaps and network breakdowns.