Successfully introducing Data Mesh: tailoring data domains in insurance

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suchona.kani.z
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Successfully introducing Data Mesh: tailoring data domains in insurance

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When dealing with the data mesh approach, the question quickly arises as to which criteria the data domains should be tailored to. Unfortunately, there are only vague suggestions in the literature and key questions often remain unanswered, which can leave projects in uncertainty.

This blog post presents initial evaluation frameworks for the above-mentioned issue. The aim is to contribute to a well-founded professional discussion.

Data Mesh – Data teams (domains) are responsible for their data products
The data mesh approach, introduced by Zhamak Dehghani in argentina consumer email list her book "Data Mesh: Creating a Modern Data Architecture", is a concept that aims to reduce the complexity of data management in enterprises and improve scalability and agility. In this approach, data is treated as discrete and autonomous entities.

In the data mesh, data products are viewed as central objects that are developed, maintained and managed by self-organized, interdisciplinary teams. These teams are called "data domains" and are responsible for specific business areas or data areas. Each data domain is independent and has full control of its data products - including defining data quality, security and access policies.

Communication and collaboration between the data domains takes place via a decentralized governance structure based on clear interfaces and standards. These include uniform metadata models, data catalogs and platforms that facilitate the exchange and reuse of data products.

The data mesh approach is a good basis for modern technologies such as cloud computing, big data and artificial intelligence (AI) to process data more efficiently and make it usable for a wider range of users.

Evaluation criteria – a first step towards successful data mesh implementation
For a successful introduction of a data mesh concept or an efficient tailoring of the data domains, the following criteria should be taken into account when making a decision:

1. Business domain orientation
2. Clearly defined responsibilities
3. Autonomous data teams
4. Technological independence
5. Clearly defined interfaces and APIs
Business domain orientation – enables effective data management
In an insurance company, claims processing may be a business domain. The data domain can be tailored to focus on information such as claim reports, claim amounts, customer information, and claim history. This enables effective management and analysis of claim data to identify trends, detect fraud, and optimize the claims processing process.
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