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Data mesh is a sociotechnical approach to building a decentralized data architecture by leveraging a domain-oriented, self-serve design (in a software development perspective), and borrows Eric Evans’ theory of domain-driven design [1] and Manuel Pais’ and Matthew Skelton’s theory of team topologies. [2]
A research design typically outlines the theories and models underlying a project; the research question(s) of a project; a strategy for gathering data and information; and a strategy for producing answers from the data. [1] A strong research design yields valid answers to research questions while weak designs yield unreliable, imprecise or ...
range data [16] Fertility 2009 AIM@SHAPE Repository (scanned at Utrecht University) Small stone statue with two joined figures. 241,607 vertices 483,226 triangles Laser scan. Nefertiti 2015 Nora Al-Badri and Jan Nikolai Nelles A stoneworked bust of the Egyptian queen Nefertiti was created in 1345 BC by Thutmose ~2 million triangles CC By SA 4.0
An algorithm generating a mesh is typically controlled by the above three and other parameters. Some types of computer analysis of a constructed design require an adaptive mesh refinement, which is a mesh made finer (using stronger parameters) in regions where the analysis needs more detail. [1] [2]
The design is flexible, scalable, consistent and adaptable to the needs of the enterprise" [11] Data vault's philosophy is that all data is relevant data, even if it is not in line with established definitions and business rules. If data are not conforming to these definitions and rules then that is a problem for the business, not the data ...
Snowflake schema used by example query. The example schema shown to the right is a snowflaked version of the star schema example provided in the star schema article. The following example query is the snowflake schema equivalent of the star schema example code which returns the total number of television units sold by brand and by country for 1997.
For example, a company might wish to summarize financial data by product, by time-period, and by city to compare actual and budget expenses. Product, time, city and scenario (actual and budget) are the data's dimensions. [3] Cube is a shorthand for multidimensional dataset, given that data can have an arbitrary number of dimensions.
With a large sample of sensor data, analytics processing can be used to make sense out of these data. The connectivity of wireless sensor networks rely on the principles behind wireless ad hoc networks, since sensors can now be deploy without any fixed radio towers, and they can now form networks on-the-fly.