Oliver Rothland
Trainer and Solution Architect for Data Management, Data Mesh, Data Fabric, Observability, Big Data Technologies, Advanced
Experience
Trainer and Solution Architect for Data Management, Data Mesh, Data Fabric, Observability, Big Data Technologies, Advanced
Supporting national and international companies in building data-driven processes, methods, systems and applications (data-driven company) in the area of data management and agile requirements engineering.
Identifying essential use cases and (non-functional) requirements to build an architecture on one hand.
Optimizing the client's internal processes and developing training plans for new technologies and methods.
Combining technological know-how (for example, for data analysis in cloud data analytics environments over semantic layers) with important soft skills such as agility, teamwork, creativity and analytical competence.
Focusing in the area of data management on the efficient use of systems as well as the easy use of technologies for data engineering, for data cataloging, virtualization, exploration and visualization.
Operationalizing both infrastructure and data and mathematical, analytical models (DevOps, DataOps, MLOps).
Acting as a link between architecture, business units, development and operations, taking into account essential core areas such as data governance, data security and data quality.
Summary
Oliver Rothland has been working for over 25 years in the field of data management and agile requirements engineering, supporting national and international companies in building data-driven processes, methods, systems and applications (data-driven company).
To successfully execute projects, Oliver Rothland supports his clients in identifying essential use cases and (non-functional) requirements to, on one hand, build an architecture and, on the other hand, optimize the client's internal processes and develop training plans for new technologies and methods.
As a trainer and solution architect for data management, data mesh, data fabric, observability, big data technologies, advanced analytics methods and agile development, he combines technological know-how (for example, for data analysis in cloud data analytics environments over semantic layers) with important soft skills (such as agility, teamwork, creativity and analytical competence) to make solutions usable and tangible.
In the field of data management, his focus, alongside the efficient use of systems, is on the simple use of technologies for data engineering, for data cataloging, virtualization, exploration and visualization, and on operationalizing both infrastructure as well as data and mathematical analytical models (DevOps, DataOps, MLOps).
With his extensive experience in enterprise and cloud data management environments, he acts as the link between architecture, business units, development and operations, considering key core areas such as data governance, data security and data quality.
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