While the need for data integration will differ between organisations, there is still a core checklist on ensuring the data integration strategy will be a success. A successful data integration strategy will:
- align with your business goals,
- save time and resources when building integrations,
- minimise business disruptions,
- lower risk by centralising data governance and data management,
- enable a faster response to risks, and
- enable better agility in times of change.
In essence, successful data integration is not just about the immediate transfer of data; it's a comprehensive system designed with a focus on past learnings, present requirements, and future aspirations, ensuring every step aligns with the broader business objectives.
Choosing an approach that achieves success for your organisation is a balancing act. Which data integration approach you use will heavily depend on exactly what your business wants to achieve and what it will find value from. There are certain aspects that you should be on the lookout for when considering a modern data integration platform, including:
Capacity
Regardless of the scale of the project, there is a need for your chosen data integration platform to be able to process ever-growing volumes of data. Organisations now have more data than ever before, so being able to process an increasing amount of data needs to be an essential consideration for any enterprise-scale organisation.
Connectivity
Many organisations may favour data integration approaches that boast an exhaustive portfolio of dedicated connectors supporting both legacy and modern sources. While modern methods are excellent at connecting to various data files and APIs, it’s important to be on the lookout for solutions that seamlessly integrate with your existing systems and don’t compromise on compatibility with traditional data formats.
Compatible
A robust data integration solution should have an extendable and open architecture. This is vital because modern integration platforms need to support a variety of integration scenarios and environments, including on-premise, cloud, hybrid, and multi-cloud, depending on your deployment model. Where some tools may excel in single-environment integrations, it's important to be on the lookout for solutions that can adapt and grow with your evolving infrastructure needs.
Low Code
Low code development with flexible and scalable architecture facilitates rapid generation of projects as there’s a reduced need for extensive coding knowledge. Unlike older, code-heavy tools, modern platforms enable significant achievements with minimal coding expertise. Where some platforms demand deep programming skills, modern approaches have less of a need for team members to be proficient in every coding language, it's important to look for those that make data integration accessible to those with limited coding experience.
Unified
Another critical feature to consider is a single technology that federates all forms of data integration, including Big Data, NoSQL, API, IoT, and more. This should encompass capabilities for real-time streaming, event-based integration, and batch processing. While older integration tools may have been limited to just batch processing, contemporary solutions should offer a more comprehensive range of functionalities.
Consistent
Consistency in design across different project types is vital for the seamless transfer of teams from one project to another. Tools like data connectors and templates maintain this consistency as integrations and architectures evolve. These features allow for the reuse of templates and code across multiple projects, eliminating the need to start from scratch – a common requirement with traditional tools. This approach not only streamlines the integration process but also removes many complexities associated with individual builds, offering a more modern and efficient way to handle data integration.
Adaptable
Besides ensuring consistency, templates also offer adaptability. Fully customisable templates support unique requirements and adapt to underlying technological changes. This allows amendments for new integration requirements or data sources, enhancing efficiency and saving time that would otherwise go into extensive rework. Access to such templates can lead to significant savings in resources – time and manpower – making the process more efficient. Furthermore, template design components that offer out-of-the-box capabilities can save teams valuable implementation time.
Efficient
Continuous integration and deployment (CI/CD) work seamlessly with external DevOps tools, streamlining and accelerating the software development lifecycle. CI/CD practices help to avoid bugs and code failures while maintaining a continuous cycle of software development and updates. This method resolves the issue of multiple software versions, giving the wider team access to the most current version rather than individual, potentially outdated copies.
Previously, without CI/CD, concurrent work on the same project may have been challenging, necessitating a more rigorous and controlled process. Unvetted changes could disrupt a live version. CI/CD allows for safer promotion of code between different environments, such as production and testing, a task more complicated or even chaotic with older tools lacking a centralised code repository. Without such centralisation, there's a higher risk of human error and difficulties in collaborative work, making CI/CD an essential element in modern development workflows. Where some tools may not offer such integration, it’s important to look for solutions that support CI/CD, ensuring a smoother, more collaborative, and error-resistant development process.
Business-Centric
Business-centricity in data integration approaches involves transforming business rules into deployable code, crucial for effective data handling. Modern platforms align integration processes with an organisation's strategic goals, ensuring a close connection between business needs and technical execution. Unlike older systems, modern data integration platforms are designed to facilitate this alignment, making it easier to translate business objectives into practical data solutions. When choosing a data integration platform, it’s important to select one that offers a strong business-centric approach, ensuring that the platform supports and enhances the organisation's overall objectives.
Whether you're adopting a modern data management approach like Data Mesh or Data Fabric - or simply trying to improve the availability of data to those that need it - a best-in-breed data integration platform is an essential ingredient. Whilst there are an abundance of data integration techniques and approaches, there are certain aspects that you should be on the lookout for from a modern data integration platform.
The attributes listed above can be seen in data integration solutions such as Semarchy xDI, whose platform offers a structured, adaptable and reliable approach to data integration. xDI's breadth of capabilities empower organisations to seamlessly connect disparate data sources whilst driving efficiency, insight, and competitive advantage. Through templating in xDI, the re-use of existing integrations is made easy, but it also allows for adapted or updated integration flows, streamlining the data integration development process and improving agility, flexibility and consistency.
We’re here to help organisations choose the right approach - or blend of approaches - to suit their business objectives and empower them to make more data-led decisions in a unified, cohesive manner.
Amplifi have put together some top tips for 3 steps to better integration which you can read here, or get in touch today to see how Amplifi can help, no matter where you are on your data integration journey.
