DWautomatic is a powerful, metadata-driven tool for seamlessly integrating new source systems into your data warehouse. The tool includes features such as delta detection, versioning, historization and simple transformations of incoming data, all achieved through a generic metadata-driven approach.
DWautomatic is a powerful, metadata-driven tool for seamlessly integrating new source systems into your data warehouse. The tool includes features such as delta detection, versioning, historization and simple transformations of incoming data, all achieved through a generic metadata-driven approach.
The development and maintenance of ETL programs is the biggest cost driver of DWH projects. For this reason, many companies have decided to use an ETL tool such as Ab Initio, IBM InfoSphere DataStage or Informatica PowerCenter. The strength of such tools lies in their ability to map complex business logic in transformation programs (often a core task in data warehouse projects).
In addition to these tasks, however, we are increasingly finding in data integration projects the requirement to integrate new source systems into the DWH, where the data structures in the DWH are similar to the structures of the source system, but delta detection, versioning/historization and simple transformations are to be carried out; in addition, automatic detection of structural changes and their propagation is often required. The growing importance of these desired functionalities goes hand in hand with the increasing spread of the data vault approach. Some ETL tools are often not particularly suitable for these tasks.
Metadata-driven implementation of transformation and load functions
Automatic identification of structural changes/extensions
Identification of new data content using CDC and own control
Generic implementation of structural changes/extensions
Automated historization and versioning of data
Creation of an auditable data warehouse
Adapted to the Data Vault modeling approach
Optimized for various RDBMS, for high-performance parallel processing
In the manufacturing industry, DWautomatic can help to seamlessly integrate various data sources such as production facilities, suppliers, inventory and sales information into the data warehouse. Through delta detection and accurate historization, companies can better understand their supply chains, identify bottlenecks and improve efficiency.
Quality assurance is of crucial importance in the industrial sector. DWautomatic enables the integration of data from sensors, production systems and quality inspections. With this tool, companies can identify error patterns, analyze quality trends and optimize processes to prevent or eliminate errors.
By integrating data from IoT sensors on machines and systems into the data warehouse, companies can develop predictive maintenance models. DWautomatic supports this process by enabling the continuous collection and analysis of sensor data to predict maintenance needs and minimize unplanned downtime.
Timofej Lisow ist ein erfahrener Physiker und Senior Consultant bei synvert saracus. Seine Spezialisierungen umfassen Softwareentwicklung, ‑architektur, AWS und DevOps. Mit umfangreichem Wissen und Erfahrung in diesen Bereichen, einschli...
Ulrich Hebestreit hat Mathematik studiert und beschäftigt sich seit 30 Jahren mit allen Fragen und Aufgaben zum Thema Software-Engineering. Sein besonderer Schwerpunkt ist seit über 20 Jahren die Architektur, Konzeption und Realisierun...
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