Data architecture | EPFL Graph Search

Data architecture consist of models, policies, rules, and standards that govern which data is collected and how it is stored, arranged, integrated, and put to use in data systems and in organizations. Data is usually one of several architecture domains that form the pillars of an enterprise architecture or solution architecture. A data architecture aims to set data standards for all its data systems as a vision or a model of the eventual interactions between those data systems. Data integration, for example, should be dependent upon data architecture standards since data integration requires data interactions between two or more data systems. A data architecture, in part, describes the data structures used by a business and its computer applications software. Data architectures address data in storage, data in use, and data in motion; descriptions of data stores, data groups, and data items; and mappings of those data artifacts to data qualities, applications, locations, etc. Essential to realizing the target state, data architecture describes how data is processed, stored, and used in an information system. It provides criteria for data processing operations to make it possible to design data flows and also control the flow of data in the system. The data architect is typically responsible for defining the target state, aligning during development and then following up to ensure enhancements are done in the spirit of the original blueprint. During the definition of the target state, the data architecture breaks a subject down to the atomic level and then builds it back up to the desired form. The data architect breaks the subject down by going through three traditional architectural stages: Conceptual - represents all business entities. Logical - represents the logic of how entities are related. Physical - the realization of the data mechanisms for a specific type of functionality. The "data" column of the Zachman Framework for enterprise architecture – In this second, broader sense, data architecture includes a complete analysis of the relationships among an organization's functions, available technologies, and data types.

DBFS: Dynamic Bitwidth-Frequency Scaling for Efficient Software-defined SIMD

Giovanni Ansaloni, Alexandre Sébastien Julien Levisse, Pengbo Yu, Flavio Ponzina

Machine learning algorithms such as Convolutional Neural Networks (CNNs) are characterized by high robustness towards quantization, supporting small-bitwidth fixed-point arithmetic at inference time with little to no degradation in accuracy. In turn, small ...

2024

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Danick Briand, Nicolas Francis Fumeaux

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Zenodo2024

Sediment and large wood supply in proglacial streams: insights from the Upper Navisence catchment monitoring.

Christophe Ancey, Ivan Pascal, Bob de Graffenried

Preliminary analyses of data collected during 2023 and analyses of archived data provided new insights into the sources of wood and sediment in this river corridor. These analyses have highlighted the primary supply processes accountable for these material ...

2023