Datensystems

Datensystems, or data systems, are information systems that collect, store, process, and provide access to data to support the operations, decision making, and communication needs of organizations. They integrate hardware, software, data, people, and processes into a cohesive platform for data management.

Core components include databases or data stores, database management systems (DBMS), data models, and the interfaces used by users and applications to access data. They support transactional processing (OLTP) as well as analytical processing (OLAP), or both. Deployments range from centralized systems to client-server architectures and modern cloud-based or distributed configurations.

Common data models include relational, NoSQL (document, key-value, columnar), graph, and columnar/analytic models. Data architectures often combine operational systems with analytical repositories, such as data warehouses for structured, integrated data and data lakes for large-scale, diverse data. Trends include data meshes and data fabrics to improve scalability, governance, and domain-oriented access.

Data management covers data modeling and database design, data quality and lineage, metadata management, data integration and ETL/ELT, and security and privacy, including access controls and regulatory compliance.

Interoperability relies on standards and interfaces, such as SQL, APIs, and common data formats. Concepts like schema-on-write (typical for warehouses) and schema-on-read (typical for data lakes) influence organization and usability.

Use cases include transactional processing, business intelligence, data warehousing, and advanced analytics. Challenges include data silos, governance gaps, security risks, and keeping data current in dynamic environments. Ongoing evolution features cloud-native platforms, automation, and AI-assisted data management.