The acceleration of your business\u2019 digital aspirations depends on fast, connected and reliable data flows. This need will be amplified in the post-COVID era where the transition to digital customer channels, business models and remote working is expected to accelerate. In this two-part series, we will explore how AWS can enable modern data integration patterns and overcome the cost, time and operational inertia of implementing these using traditional approaches.\nData Integration in the Digital Era\nBusinesses are more connected than they have ever been \u2013 with their customers, suppliers, partners, regulators, staff, facilities and assets. This is underpinned by a shift towards real-time insights and decisioning. Data integration and information exchange is a key enabler of solutions ranging from novel customer experiences and intelligent business automation to the disruption of entire industries and business models.\nThe pace of innovation is accelerating and enterprises need mature technology platforms that are feature-rich, economical, secure, performant and reliable if they are to excel. A critical component is the modern enterprise data integration platform, which provides the services enabling the timely flow of data from where it is generated to where it is consumed.\nPlatform-of-Best-Fit\nEnterprise data integration requirements are not all equal. Differences in data types, volumes, sources, targets, business criticality, time-sensitivity, data security and governance call for purpose-fit Enterprise Integration Patterns.\nFor decades, organizations have invested in one-size-fits-all data integration technologies. However, enabling the many and varied integration patterns requires a significant investment in specialist platforms (see figure 1). It is expensive, time-consuming and operationally difficult to provision and manage these, particularly in on-premises environments. These enterprises often find themselves compromising on a platform-of-all-fit, resigned to technologies that can support a broader number of needs but not necessarily excel at any. It results in compromised technical solutions that under-meet business needs and dilute benefits.\n AWS\n\nFigure 1 A reference model depicting the array of specialist integration platforms needed to support diverse integration scenarios and deliver class-leading data integration outcomes.\n\n\nAWS offers a broad and deep set of features, allowing businesses to access capabilities that best support their requirements. The platform bridges the gap between the connectivity aspirations of today\u2019s enterprises and their capacity to buy, provision and run the enabling technologies themselves.\nAs a result, AWS enables a platform-of-best-fit. It avails purpose-fit services that can be composed together to implement integration patterns that are effective, reliable, secure, performant, flexible and cost-effective, without the burden of managing all of the platform provisioning and operational activities.\nBusiness Benefits\nThe economics of adopting AWS integration services are highly compelling. There are three commercial dynamics at play:\n\nOrganizations do not need to invest large sums of capital up front to provision these platforms. Instead, they only pay for the services as they use them and for the capacity that they consume, on a variable, no lock-in basis.\nThe elasticity of these cloud services and their capacity to scale automatically based on volume and consumption alleviates the need for organizations to over-provision their infrastructure and pay for idle capacity that exists only to cater for potential volume spikes.\nAWS, with its global footprint and active base of over 1 million customers, can realize economies of scale that most individual organizations cannot. These manifest in lower prices for many organizations.\n\nAs compelling as the economics are, the most beneficial aspect of these AWS integration services is the agility and speed with which they enable organizations to run and the experimentation and innovation that they liberate as a result. There are two dimensions of this.\n\nFor many organizations, the aspiration to innovate can be hindered by the financial investment needed to furnish the requisite technology platforms or the time and effort needed to justify and secure said funding. By reducing the investment required to try new ideas, AWS promotes incremental experimentation in a way that is limited by traditional platforms.\nAWS integration services can be provisioned, scaled, expanded globally, retired and replaced in minutes. As shown in figure 2, by transferring to AWS the undifferentiated heavy lifting of provisioning infrastructure, installing and configuring software, managing capacity, administering patches, performing backups and organizing availability, organizations free up their valuable engineering resources to focus on activities of most value and differentiation \u2013 solving business problems, not infrastructure ones.\n\n AWS\n\nFigure 2:\u00a0 Accelerating the time to value by relieving resources of the undifferentiated heavy lifting of provisioning and running their own integration platforms.\n\n\nBroadest and Deepest Platform\nAWS offers a broad catalogue of services and enables the most common data integration scenarios.\nTo demonstrate the depth of capability offered by these services, stay tuned for part two of this series, where the use of SQS, SNS and Kinesis Data Streams to enable point-to-point messaging, publish-subscribe messaging and real-time streaming patterns will be explored.\n AWS\nKey Takeaway\u00a0 \nIncreasingly divergent data flows and demands for more real-time connectivity necessitates platforms with broader and deeper functionality, but furnishing and managing these in a traditional or on-premises context adds complexity and overhead. Adopting a cloud-native integration architecture, using a mature and feature-rich platform capable of serving established integration patterns, frees organizations from the burden of operating platforms and allows them to focus on value-add data innovation and engineering.