Digitization, the use of AI and new data-oriented business models have increased the demand for data quality enormously. Conventional master data management tools are often no longer sufficient. In order to implement the much-cited data governance – i.e. a concrete concept of how data is to be handled – an intelligent “data hub” is required today.

Data can only be useful if it is distributed and brought to life in the specialist departments. AI also only works with high-quality data. Data governance (i.e. standards, processes and roles for the secure and transparent use of information) are sensitive issues, especially in Germany with its high standards of data protection and data security. Centralized governance is required to ensure this, or to put it another way: an intelligent data hub.

There are numerous use cases in master data management, typically found in Germany in small and medium-sized companies. In view of increasing compliance requirements and in the course of digitization, it is becoming increasingly difficult for these customers to have their data quality under control, i.e. to have clean and up-to-date data. You therefore need a data management platform that offers a high level of functionality while at the same time being easy to use.

Ideally, Master Data Management, Application Data Management and Collaborative Data Governance are combined in an agile platform – in a so-called “Intelligent Data Hub”. This allows data models, mappings and applications to be designed and implemented in one place and data management initiatives to be carried out holistically. Semarchy then creates a “golden record” (or “single point of truth”) from all connected data sources (“repositories”). The next step would then be to move from the syntactic to the content check, i.e. to classify the meaning of a data record in different contextual connections.

Such a platform leverages algorithms, intuitive workflows, and UX design to simplify data management, quality, enrichment, and workflows. Implemented via an agile and iterative approach, it delivers usable results almost immediately and at the same time can be easily adapted to the complexity of the company. Any databases and services are connected via standard APIs, the code-free configuration of user interfaces, queries and workflows allow teams to work quickly.

In 2021, Gartner has a total of 16 Master Data Management (MDM) solutions in its portfolio Magic Quadrant listed. In Germany there are two attractive target groups for these solutions: medium-sized companies that have recognized that they need to pay more attention to the topic of data management, and large companies with a high degree of maturity that should be supported in the further development of their data management concepts.