Homogenization
Data homogenization refers to the process of standardizing or normalizing data to ensure consistency and uniformity across different sources, formats, or representations. The goal is to create a unified and standardized dataset, making it easier to analyze, compare, and integrate information from diverse origins. Data homogenization is particularly important in data integration, analytics, and business intelligence, where data may come from various systems, databases, or sources with differing structures and formats.
References
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Make data uniform, consistent, and comparable.🔗dagster.io -
Digital Twin System enables the communication and semantic data exchange between all different stakeholders across the life cycle of a product🔗Metrology and Quality News - Online Magazine -
https://www.bosch-connected-industry.com/de/media/en/whitepaper_1/wp_datenhomogenisierung/whitepaper_datenhomogenisierung_de.pdf🔗bosch-connected-industry.com -
In this article, we look at the importance of data quality in an ever expanding world of information. We explore step-by-step how reliable data quality processes are built and executed to help organisations retain the value of the data they own.🔗Clariba website