Integrating disparate IT systems inside an organization can be akin to trying to get a crew of people who don't speak the same language to row a boat together - extremely difficult. There are so many obstacles to overcome when trying to get these systems to work together smoothly, from working with systems using completely different data formats and APIs to having to comply with regulatory issues.
Upfront, it can be overwhelming. While it's possible to overcome these hurdles to integration with some careful planning to map out all the differences, good communication to bridge gaps, and then step-by-step execution to tackle issues, it's a slow and steady process. Making heterogeneous systems into one unified platform is possible, but it requires some vision, patience and perseverance. As with that hypothetical crew, the right integration approach can get disparate IT systems rowing together.
The first step towards successful integration is gaining a clear understanding of the existing IT landscape. What systems are currently in use? How do they interact with each other? What data and functionality do they provide? By gathering this foundational knowledge, IT engineering services can map out how systems need to communicate and where potential pitfalls may emerge.
Create a master list of all systems that need to be integrated. This includes not just core business applications but also supplementary tools for tasks like reporting, analytics, IT service management etc. Document the interdependencies between systems so you understand how they currently share data and functionality.
Do an gap analysis of how data is structured and accessed across different systems. Look for inconsistencies in data schemas, APIs, and protocols that need to be addressed to allow communication between systems. For example, RESTful APIs vs SOAP web services.
Factors in any regulatory compliance needs that dictate how systems are accessed, who can access data, how it is transferred, monitoring requirements, etc. These constraints guide how flexible and open integrations can be designed.
Once you understand the as-is state of systems, clearly define integration requirements and priorities to drive project planning.
Functionality and Data Requirements. Outline the key functionality and data that needs to be integrated between systems based on business needs. These are the use cases that integrations must support.
Priority Integration Workstreams. Not all integrations may be tackled at once. Define priority workstreams based on which systems deliver the most value if integrated first. Subsequent workstreams can build on the foundations established earlier.
Future Flexibility Requirements. Build in requirements to support easy onboarding of new systems and tools down the line. Integrations need to be designed for expandability by externalizing access points through APIs and message queues.
Transitioning data between disparate systems and consolidating data stores is an intricate process that needs oversight.
Data Mapping Across Systems. Map data fields across systems to each other to create data dictionaries. This helps identify data equivalencies as well as gaps that need to be addressed.
Data Transformation Pipelines. Design automated, repeatable data pipelines that take source data, transform it to the required shape and load it into the destination system. This is key for large-scale data migration efforts.
Master Data Management. Implement master data management to have a single source of truth across systems. This involves consolidating duplicates, resolving conflicts and maintaining data integrity.
Getting systems to 'talk' to each other requires making communication protocols, messaging formats and APIs compatible.
API Management. Use API management tools to expose core system APIs in a standardized way. This abstracts the underlying complexity behind consistent APIs.
Common Communication Protocols. Establish common ground between systems by using widely adopted protocols like REST, JSON, WebSockets, AMQP etc. Shared protocols are easier to integrate.
Message Transformation Logic. Where required, handle the transformation of messages and protocols between source and destination systems so they can communicate without having direct compatibility.
Integrating access and identity across systems is key for security, governance and compliance.
Role-Based Access Mapping. Map user roles and access levels between integrated systems to ensure appropriate controls remain in place post-integration.
Federated Identity. Implement single sign-on by federating identity across integrated systems. This allows unified access control across the environment.
Maintaining Compliance. Adhere to regulatory compliance requirements when exposing data through integrations. Record data access, enforce encryption etc., as needed.
Once live, the integrated landscape needs to be proactively monitored to maintain health.
Transaction Monitoring. Monitor key transactions via logging or APM solutions to analyze performance metrics. Rapidly detect integration issues causing bottlenecks or failures.
Automated Alerting. Configure alerts on critical integration failures, performance degradations, etc., so teams are automatically notified of issues.
Operational Dashboards. Build operational dashboards with key integration health metrics like uptime, data rates, error rates to maintain a real time view.
Manage growing integration complexity by adopting practices like API-led connectivity, containerization and orchestration.
API-Led Connectivity. Embrace API-led connectivity to abstract complexity behind reusable APIs instead of point-to-point integrations. APIs ease onboarding, too.
Containers and Microservices. Deconstruct monoliths into containerized microservices that integrate via APIs. This improvesthe maintainability and scalability of integrations.
Integration Middleware. Utilize integration middleware or an ESB to remove friction when connecting disparate systems using message queues, data mapping, and APIs.
API and Event Gateways. Leverage gateways to manage, orchestrate and monitor events and APIs across systems while enforcing policies consistently across the environment.
Do not try to boil the ocean. Carefully sequence integration projects to provide incremental business value without overloading teams.
Minimum Viable Integration Product. Focus the initial integration on delivering core functionality and data that brings tangible business value. Avoid scope creep.
Building Slowly But Surely. Plan incremental work phases that gradually enhance integrations instead of replacing all systems at once, which is high-risk and disruptive.
Learning Before Expanding. Use feedback and lessons from initial workstreams to guide architecture decisions and improve processes before adding more systems to the integration.
IT system integration projects have many technical and organizational challenges. But if we take time to evaluate the current landscape, play to our business priorities, orchestrate data, enable communication between systems, monitor operations, and practice agile, we can get past these hurdles. It should ensure that each incremental phase shows business value so that the enhancement of integrations continues incrementally over time.