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The Future Of Integration Is Being Defined By Scalable, Service-Oriented Architectures

March 5, 2017
  • Accelerating every business process that impacts customers is more important than moving the data around that supports them.
  • The key to winning customers is giving them excellent experiences based on real-time, accurate and contextual data that stays in step with them over time.
  • Gaining new insights into how every business process impacts a customer is only possible with service-oriented architectures and frameworks.

Delivering Real-Time Intelligence Is The Future Of Integration

The speed that customers are reshaping businesses is completely redefining integration strategies today. Tightly coupled integration points enabled by ETL and other rigid frameworks create roadblocks that make customer responsiveness nearly impossible. Legacy data integration platforms that move data synchronously can’t scale to the speed and responsiveness customers want today.

In reality every company’s competitive strength is measured on how responsive they are or not. Legacy integration technologies are becoming more of a liability than an asset every day. All companies are beginning to realize they compete on time now more than ever. And when that happens, all realize that legacy integration roadblocks do more than just slow down reporting, they hurt customer relationships. These factors are driving an entirely new series of dynamics in the enterprise integration arena defined below:

Real-time integration allows companies to compete on time as fiercely as would pricing, products and services. 

To make time a competitive strength, real-time intelligence is critical. That’s the cornerstone of the future of integration. Being able to connect to a diverse range of legacy systems while retaining and improving core business processes is key. Loosely-coupled web services that can be combined to create a scalable service-oriented architecture is the future of legacy integration.

Zero latency is quickly becoming the new normal – just ask Amazon. 

Today every company wants to provide an online experience comparable to Amazon. In two clicks it is possible to buy anything on the site, and the same experience holds true across all devices the site is accessible from. What’s behind the success of Amazon is a service-oriented architecture or framework enabling zero latency catalog updates. Using web services that consume catalog, pricing, availability and shipping data, the person buying online receives a massive amount of data in seconds during their web shopping session. Contextually relevant, precisely personalized to their preferences, priced competitively and available now, Amazon makes the sale in seconds. It all starts with zero latency in their services architecture and leads to delighting another online customer.

Deploy a service-oriented framework to achieve the real-time intelligence every company needs to stay relevant. 

The essence of a service-oriented architecture or framework is synchronized communication across a series of web services and intelligent objects. By taking a service-centric approach that can flex to the needs of business processes, CIOs and line-of-business leaders can partner with each other to turn analytics into real-time intelligence. Moving faster than competitors with greater insight keeps a company competitive and relevant to the customers it serves. And it’s only possible when a flexible, scaleable services oriented approach to integration is adopted company-wide.

The future of analytics and business intelligence is service-based

Transitioning to a services-oriented architecture delivers benefits to companies they weren’t expecting. Insights into which business processes are working the most efficiently, which are in need of re-engineering and which are best eliminated Making analytics pervasive across all business processes for the first time becomes possible. Bench-marking business processes become commonplace. And best of all, customer responsiveness and retention go up. For any business process to improve there needs to be a services-oriented architecture or framework in place to grow from.

Using analytics strategies for solving complex problems requires service-oriented architectures. 

Machine learning’s potential to revolutionize problem-solving using high-speed algorithms that optimize outcomes based on constraints only will work in service-oriented frameworks and architectures. Machine learning’s potential is being realized across a wide range of applications including imaging, natural language processing (NLP), logistics and supply chains today. Investing in a service-oriented architecture opens up the potential to use this and other advanced technologies to gain greater insights into operations.