At Metyis, we take on the design and development of the data landscape and deliver data products with their engagement. Data architecture implementation can come in the form of a data warehouse, data lake, lakehouse, data hub, or data mesh. This includes the migration of all data-related services into the main cloud providers.
This includes the development and maintenance of data pipelines and data ingestion frameworks. We take on the implementation and maintenance of data models with the integration of data sources into the company landscape.
We fully implement the data lifecycle. We aim for data quality with the development and automation of testing processes. Pseudo/Anonymisation, masking and other data protection processes are also implemented. We use a data catalogue and data dictionary building, all whilst considering GDPR-related activities.
Our approach includes data activities leadership, data insights, self-service analytics and data quality monitoring.
For the data infrastructure, we implement cloud and network security. We manage role, policy, and attributed-based access control. We monitor data exploration, consumption, and sharing processes with full data product security.
We implement project and product management practices, along with a software development culture. We engage the data-driven culture and process automation whilst building sustainable and cross-functional data teams.