In the area of dedicated information systems, we model structures and levels for data management and transformation along your process chains. Traditional data warehouse concepts and ETL processes are extended or transferred into data lake concepts and ELT approaches.
Depending on the character of the data, the requirements for the final quality of the processed data, the urgency of the task and the long-term needs, different concepts come into play. This results in domains of varying data quality – from raw data, no or little curation, finest granularity, and maximum timeliness, up to strictly curated data in terms of traditional data warehouse concepts. Depending on the requirements and application scenario, all gradations in between are also possible.
We cover the traditional data warehouse and data mart concepts according to Inmon and Kimball, data vault modeling (CDVP2 certified) according to Linstedt as well as modern lambda architectures and successor concepts for real-time processing, real-time analysis, streaming, and IoT requirements.
Our services also include the development of complete automation frameworks for the metadata-driven generation of structures and data transformation packages, process chain control, error handling, logging and monitoring as well as application life-cycle management with all aspects of development processes from source code management, testing, deployment, automation to “continuous integration.”