data level

data level

[′dad·ə ‚lev·əl]
(computer science)
The rank of a data element in a source language with respect to other elements in the same record.
References in periodicals archive ?
Dark fibre is an optical fibre that users can access at the optical data level rather than the electrical data level as in conventional communications networks.
As data breaches multiply, more businesses are looking at data level strategies to protect their customers and assets from threats inside and outside the organization.
The architecture of production route system consist from the following levels: Input data level, Operational data level and New order route elaboration level as presented in Figure 1.
The company said that NovaView for PowerPivot brings unique self-service BI capabilities like intuitive web interface, advanced analytics and a data level security layer, providing new ways for analysts and information workers to generate insights and make better decisions.
growing interest in continuous auditing and data level assurance, and other market factors, the need for XBRL GL is increasingly obvious.
The software includes a new tool called Query Builder, which is fully integrated and allows users to produce disaggregate data reports at the most detailed data level.
On the data level, it is a more comprehensive solution for data storage management than alternatives.
That is, the expansion and re-alignment of the occupational structure (based on further vocational research, refined vocational theory, more precise measurements, and a better understanding of the relationships among different occupations) can be accomplished easily at the data level without having to rewrite the search/match routines of the computer program.
The Verdasys Digital Guardian Framework creates a data level perimeter that assures that data is controlled by policy and monitored for accountability, establishing a community of trust between the data user, data owner and data provider.
This is a first for multi-government agency communications, and extends data level security outside the traditional organisational secure internal domain.
Based on analysis and modeling we suggest that routing data storage and search framework should be consist of following levels: Input data level, Data storage level, Data analysis level, and Output data level represented in the Figure 2.
In today's IT market, the real value to an organization is located at the data level.