Keep your data up to date and available in all your systems – unrestricted and in real time. Transform your data exactly according to your requirements. Simple to complex ETL processes of any kind can be easily implemented with the Enterprise Data Platform.
You can manage processes and make all relevant data available in your systems by synchronizing all relevant systems with each other. You get higher transparency through information in the right place. Your data is transformed and further synchronized in the ETL instance. Thus you improve your business processes.
Your systems can be seamlessly connected via the distributed platform. Data is all routed via the distributed platform and transformed there. You can set up complex transformation workflows such as relation resolution, data harmonization, data standardization or calculations. This enables you to seamlessly integrate your systems and make the right data – in the right format and the necessary quality – available exactly where you need it. You can also control your processes via the distributed platform.
By connecting the right points of all your systems via one platform, you get seamless data availability. Route data through the platform to the relevant endpoints and keep your systems’ data in constant, real-time sync. The Enterprise Data Platform serves as a routing and ETL instance to ensure that your data is properly transformed, if necessary, and gets to the right endpoint.
You can integrate your data, whether unidirectional or bidirectional, with systems that are hosted on-premises. It doesn’t matter which of your systems is hosted and how. You can easily implement pure cloud integrations, hybrid integrations or even from on-premises to on-premises with the Integration Platform. This enables you to connect your entire system infrastructure, regardless of the form of hosting.
If you integrate master data, it is recommended to create a golden record. This gives you a persistent ID (PID). The PID will be written back to the source systems. This way you avoid data redundancies caused by duplicates by not simply synchronizing the data into another system where it may already exist. With the PID, you can uniquely identify an object such as a contact across both systems (including the integration of any number of systems with master data of the same entity – e.g. contacts). Fewer duplicates have been proven to reduce costs – through more complete data, for example, and thus more informed decisions.
While you connect your systems and keep your data in sync, you can still validate and enrich it as you transfer it to the platform – for higher data quality across all your source systems. Easily connect external data services like Dun and Bradstreet to your platform. For example, you can use financial or risk data for enrichment. This not only gives you synchronized and consistent data, but also validated and high-quality data – for more informed decisions and better management of your processes.
Cloud, hybrid, on-premises, all endpoints, uni- and bidirectional, unlimited, secure and GDPR compliant
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The development of further integrations is no problem and can be realised quickly.
A distributed platform ensures that your data is seamlessly available and consistent across all your systems – in real time, on demand. Simple or complex transformation logics can also be implemented via the platform. These take place in an intermediate step of synchronization.
For a distributed platform, you need the DataEngine in addition to the HubEngine. The data is routed via the platform and also transformed, validated, consolidated, aggregated or enriched there. So your processes can involve both the DataEngine or run only through the HubEngine (as with the Integration Workflows).
A multitude of individual integration workflows can form a distributed platform. First, distributed platforms serve to bundle processes in your systems, their transformation logics and the routing of data. Second, the goal of a distributed platform is to make data available in all your relevant systems – in real time. Distributed platforms thus combine integration workflows with pure, non-process-driven synchronizations. Often the first step are single integration workflows, which grow in number and complexity. This usually results in a distributed platform. We speak here of the evolution of integration.
In contrast to the distributed platform, a centralized platform is not designed as a dark processing system. It is about collecting and linking the relevant customer data in one central place. This gives you a consistent and visible picture of your customer at one glance. The distributed platform makes a consistent picture in your source systems, if they are suited, possible through seamlessly available data.
