A Better Way to Do System Integrations

Overview 

Business growth often requires the team to diversify and specialize in processes requiring multiple software packages to optimize efficiency. As soon as organizations utilize multiple subsystems to accomplish business functions, they must adopt an integration methodology to synchronize disparate data sources. Such integrations allow leaders and managers greater visibility into the diverse disciplines driving their business decisions. Like assembling the pieces of a complex data, process, and decision puzzle, integrations use data to drive decisions and ultimately, outcomes. 

 Integration Turns a Security System into a Complete Solution 

Software data integration connects and normalizes the data model and resulting information from these disparate software packages. System migration is often a primary objective of system integration. Still, other organizations using multiple databases or applications storage will want to integrate different software systems to create uniformity across multiple disciplines. By merging all data into one system, teams can effectively use and analyze all aggregated information more simply. 

 

Integration Challenges 

 

Historically, organizations have required software developers to connect these systems. While these specialists can design and implement custom integration applications to meet this need, the cost of development and brittle nature of one-off solutions makes this prohibitive. Fortunately, many providers offer integration solutions that streamline the connection process between different system platforms with advancements in low-code technology. As a result, users can manage integrations, try modern technologies, and gain valuable intelligence while minimizing the cost of engineers, software developers, and specialized integrators through these tools. 

While some of these breakthroughs seem to accelerate integration capabilities dramatically, there remain many critical factors in the success of cookie-cutter integration solutions. For example: 

  • Do you want to create a new sole source of truth, or will integrated systems share their version of reality? 
  • Will you change system data inside an application, and can each support externally have altered data structures? 
  • Will all integrated systems support synchronous data reads, or is an asynchronous process required? 
  • Is business logic or algorithmic computation needed to manage the transformation of information as data models are blended?  
  • Does the volume of data play a role in system performance and perceived real-time access or responsiveness? 
  • How configurable and dynamic do these integrations need to be, i.e., do they support ad-hoc analysis? 

Moving from this initial value-based decision to integrate to the reality of each integration requires a detailed examination of the requirements and best ways to achieve lofty business goals without costing a fortune, nor risking inventing something that quickly breaks and requires constant refactoring. 


A Better Way - The Rithm Way  

 

Rithm integrations can provide data access in a variety of ways, each tailored to the need per application. The primary focus is to connect system data in a way that matches the usage of the data within the process requiring it. For example, if a requirement exists for specific data fields in real-time for a decision or task completion, then the integration must be triggered and precisely provide the incoming data objects required in that moment.  

Integrations can connect through several programming interfaces or communication protocols uniquely designed to support developers in connecting data and capabilities. This list commonly includes: 

 

  • Web APIs: 

  • Open APIs: Commonly called a Public API with no restrictions because they are publicly available. 
  • Partner APIs: Developers need a license to access this type of API because they are not available to the public. 
  • Internal APIs: Also known as Private APIs, only internal systems expose this type of API. Usage targets internal product developer use. The company uses this type of API among the different internal teams to improve its products and services. 
  • Composite APIs: This type of API combines different data and service APIs. It is a sequence of tasks that run synchronously because of the execution, not at a task's request. Its main uses are to speed up the execution process and improve the listeners' performance in the web interfaces. 

  • Web Service APIs: 

  • SOAP (Simple Object Access Protocol): This protocol uses XML to transfer data. It defines the structure of the messages and methods of communication. As in a machine-readable document, it also uses WSDL to publish its interface definition. 
  • XML-RPC: This protocol uses a defined XML format to transfer data compared to SOAP, which uses its XML format. It is also older than SOAP. XML-RPC optimization if for low bandwidth and is simpler than SOAP. 
  • JSON-RPC: This protocol is like XML-RPC, but instead of using XML format to transfer data, it uses JSON.  
  • REST (Representational State Transfer): REST is not a protocol like the other web services. Instead, it is a set of architectural principles. The REST service needs to have specific characteristics, including simple interfaces within the request and manipulation of resources using the interface. 

  

Different third-party software solutions offer one or more of these approaches for integration, and at Rithm our approach is to support all of those that provide the various capabilities required for the process. The following example shows how two source systems (Legacy System A and B) can provide data fields that help drive better decisions when coupled together in real-time. Rithm allows these hybrid data sets to live within the process and be stored in other application systems. 



 

Because Rithm is a no-code orchestration platform, integrating data between systems and into the everyday tasks and processes organizations have as their top priorities enables more than migration, visibility, and aggregation, it allows the data to drive real-time automated and selective decisions within the enterprise. Data can then be maintained as a live connection to its source or be replicated and tied to a moment in time. Since data connections through integrations can be live, pulling and pushing data can be tied to event triggers, calendared schedules, or even human-directed powers as orchestrated within the flow of work. 

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