There are many complexities that integration can resolve, but what are the other benefits? Integration provides value both on an organizational level and on an operational level; that is, if you choose the right integration tool. 

Organizational benefits

Integrating your applications across various clouds is an important step toward synchronizing your data. However, you need an integration tool that allows deployment of integration runtimes within multiple clouds. This allows you to deploy close to your applications, resulting in reduced latency times as processes run directly within the cloud and decreased costs from not needing to move data in and out of platforms.

Operational benefits

The right application tool can also yield important timesaving, cost-cutting and performance-enhancing operational benefits:

• Access any data anywhere: With organizations diversifying their application landscape (for example, adopting SaaS applications, building new solutions in the cloud) data is increasingly dispersed across multiple environments. Integration tools that deploy across these environments enable access from any system to any data in any format.
  
  
• Resolve endpoint individuality: Each system or application has its own idiosyncrasies that must be accounted for in any integration—error handling, authentication protocols, load management, performance optimizations and more. Integration tools that handle these factors "out of the box" yield tremendous gains in productivity over coding and a higher level of enterprise-class resiliency.
  
  
• Let integrators focus on integration: Purpose-built tooling can help integrators focus less on the surrounding infrastructure and more on building business logic. By addressing error recovery, fault tolerance, log capture, performance analysis, message tracing and transactional update and recovery, an integration tool enables users to create integration flows more without requiring a deep knowledge of the various platforms and domains.

As more organizations concentrate on deploying agile integration strategies, modernizing legacy systems has become a primary focus. Industry-specific examples include the following:

• Banking: By integrating customer accounts, loan applications services and other back-end systems with their mobile app, a bank can provide services through a new digital channel and appeal to new customers.
  
  
• Manufacturing: Factories use hundreds or even thousands of devices to monitor all aspects of the production line. By connecting the devices to other systems (example, parts inventories, scheduling applications, systems that control the manufacturing environment), manufacturers can uncover insights that help them identify production problems and better balance quality, cost and throughput.
  
  
• Healthcare: By integrating a hospital patient’s record with an electronic health record (EHR) system, anyone who treats the patient has access to the patient’s history, treatments and records from the primary care physician and specialists, insurance providers and more. As the patient moves through different areas of the hospital, the relevant caregivers can easily access information that they need to treat the patient most effectively.

Organizations in any industry can leverage mission-critical systems through integration:

• ERP systems: Enterprise resource planning (ERP) systems serve as a hub for all business activities in the organization. By integrating ERP with supporting applications and services, organizations can streamline and automate mission-critical business processes, such as payment processing, supply chain functions, sales lead tracking and more.
  
  
• CRM platforms: When combined with other tools and services, customer relationship management (CRM) platforms can maximize productivity and efficiency by automating a number of sales, marketing, customer support and product development functions.

In discussions about the importance of integrated applications and services in an enterprise setting, the terms "application integration" and "data integration" are sometimes used interchangeably. However, the concept and use cases behind each of these processes are very different.

What is data integration?

Data integration is the practice of locating and retrieving information from various sources while combining that information into a unified structure and view. Also referred to as batch-based data processing, data integration involves collecting an extensive amount of data over time, storing it and then eventually processing it in batches. Data integration isn't necessarily conducted in real-time. It is commonly used after processes have been completed, so it can provide administrators the data portability they need to analyze application performance over time, eliminate redundancies and ensure data consistency and quality.

How is application integration different?

Application integration is different from data integration in that it directly links multiple applications at a functional level. Application data may be linked in near real-time, allowing organizations to create dynamic and highly adaptable applications and services.

There are a number of proven application integration styles that can be used independently or in combination, from modern API-led integration where business IT assets can be exposed and discovered in a rapid and secure way to more traditional service-oriented architecture (SOA), where different applications are integrated using a communication layer or "bus" between them. This allows enterprises to orchestrate integration flows that trigger after events occur in one application to the next. Because of these real-time interactions, enterprises are able to stay agile, responding to new data feeds or performance issues as they occur, rather than after the fact.