Combining Data Platforms and Application Integration: A Unified Approach to Real-Time Business Agility

Due to digitalisation, the volume of data sources and relevant data is continuously growing for internal and external organisational data. Data has become a significant competitive advantage for organisations. At the same time, requirements for data utilisation are also increasing, focusing on data quality, timeliness for different use cases, ease of access, and data security.

Continuously tightening customer requirements, new use cases, and the utilisation of AI require the ability to recognise the opportunities offered by data and the courage to make more significant changes to enable its various usage models. Data must be seamlessly, efficiently, and securely accessible and transferable. To utilise essential data in real time, changes must also include the renewal of architecture and the development of new technological capabilities. 

Platforms seamlessly together 

Traditionally, data platforms like Data Lakes and Data Warehouses are critical in data-driven organisations. They provide a centralised, controlled environment where data can be combined, stored, and transformed for analysis. Advanced analytics solutions give businesses real-time visibility into key performance indicators.

While data platforms are essential for long-term strategic decision-making, day-to-day operations rely heavily on process and application integration. This is where integration platforms (such as iPaaS and Integration Platform as a Service) come into play, enabling real-time connectivity between systems and applications. Whether automating customer service processes, managing supply chains, or handling product information, integrations ensure that systems operate seamlessly together. 

The same data should not be retrieved multiple times  

If application integrations and data platforms operate entirely separately, the same data may be collected and synchronised multiple times across different systems. For example, customer data may be transferred to operational applications via application integrations on the integration platform. In contrast, similar data is separately collected in batches for analysis on the data platform. This creates redundancy, increases maintenance costs, and raises the risk of errors. Customers and internal users may also need consistent data depending on which system they retrieve.

Since both data and integration work often involve many of the same processes, it makes sense to break down these separate silos and combine them into a seamless whole. This approach avoids redundancy: data doesn't need to be retrieved or stored multiple times, and the same functions and processing logic don’t need to be repeated across different systems. By integrating these two areas, operations become more efficient, achieving clear synergy benefits. We can utilise the data collected in data platforms more effectively to create better data products (data-as-a-product), taking integration needs into account instead of focusing solely on reporting and analytics.

An integrated solution architecture brings many benefits  

When combining data platform thinking and traditional integration models, companies can harness the best of both worlds. This requires a unified target architecture and governance model, where data platform and application integration design and implementation are based on a joint approach rather than point solutions.

Data and integration platforms form a seamless whole in a combined solution architecture. Data platforms provide deep insights and support decision-making through analytics and artificial intelligence. Similarly, integration platforms, such as iPaaS solutions, efficiently bring necessary data from various sources, like ERP systems or CRM solutions, into the data platform by leveraging different integration styles. This enables continuous and real-time data transfer, addressing analytics and business needs. White iPaaS platforms' data transfer and transformations can be efficiently automated and managed centrally. Ready-made connectors and integration features offer powerful tools to manage and monitor the entire data transfer process. Additionally, a Data Lakehouse architecture can enhance scalability and enable real-time data processing and refinement of data products. 

In a future-proof integration strategy, various integration styles and the capabilities of data platforms are seamlessly combined. 

Controlled use of data requires consideration  

However, it’s not advisable to transfer all data to the data platform; it’s essential to consider which types of information should be moved and when it might be more practical to utilise other direct integration styles offered by the integration platform. This approach helps avoid unnecessary effort and minimises additional maintenance. 

A well-designed solution also enables controlled data sharing with users. Effective data sharing requires robust data governance, clearly defined data ownership, and high data quality, all of which modern data platforms can support. For sharing, it is often beneficial to utilise an interface within API management, allowing for monitoring and control of its usage. Furthermore, real-time capabilities can be enhanced by leveraging event-driven solutions. 

More and more companies view data as a product, recognising it as a valuable asset that can be shared, utilised, and leveraged to generate business value. 

Develop the whole

For data products to be effective, they must be easily accessible and ready for use by other teams or data consumers. For APIs, users are already accustomed to API portals where data requesters can subscribe to the interfaces they need. This enables smoother and more controlled access to data, ensuring that users can quickly find the information they require. Additionally, a data catalogue is necessary as a central tool for data management. The data catalogue facilitates the discovery and utilisation of data by providing users with a clear and organised view of available data products, their features, and their intended uses. This enhances data usability and reduces unnecessary barriers to leveraging data effectively. 

By developing data platforms, integration platforms, API management, and event architectures as a cohesive whole, companies can prepare for future technological advancements. This approach also supports the organisation’s ability to quickly adapt to changing business needs and technological requirements, which is crucial for maintaining competitiveness.

The experts from Digia contributing to this blog are:
Jonas Källström, Chief Integration Architect – Integration and API 
Antti Seppälä, Lead Consultant – Data-Driven Solutions 
Mikko Hakola, Vice President, Integration & API


Digia offers specialised consulting services to help implement integration strategies, effectively combining the strengths of data platforms, integration platforms, API management, and event-driven architectures. If interested, contact us, and let's continue the discussions 🙂