data flow

data flow

[′dad·ə ‚flō]
(communications)
The route followed by a data message from its origination to its destination, including all the nodes through which it travels.
(computer science)
The transfer of data from an external storage device, through the processing unit and memory, and out to an external storage device.

data flow

A data flow architecture or language performs a computation when all the operands are available. Data flow is one kind of data driven architecture, the other is demand driven. It is a technique for specifying parallel computation at a fine-grain level, usually in the form of two-dimensional graphs in which instructions that are available for concurrent execution are written alongside each other while those that must be executed in sequence are written one under the other. Data dependencies between instructions are indicated by directed arcs. Instructions do not reference memory since the data dependence arcs allow data to be transmitted directly from the producing instruction to the consuming one.

Data flow schemes differ chiefly in the way that they handle re-entrant code. Static schemes disallow it, dynamic schemes use either "code copying" or "tagging" at every point of reentry.

An example of a data flow architecture is MIT's VAL machine.

data flow

(1) In computers, the path of data from source document to data entry to processing to final reports. Data changes format and sequence (within a file) as it moves from program to program.

(2) In communications, the path taken by a message from origination to destination that includes all nodes through which the data travels.
References in periodicals archive ?
com)-- Devart, a recognized vendor of professional database management software for developers and DBAs, has released the new versions of SSIS Data Flow Components with support for popular cloud data warehouses: Amazon Redshift, Google BigQuery and Azure SQL Data Warehouse.
The contract is aimed to achieve standard levels of data security and for ensuring data flow speed, reported The Peninsula.
Finally, using the weights in the first principal component, we find that the largest flow contributor to GDP has become cross-border data flow in recent years.
ABSTRACT: Data flow testing is a code based testing technique that uses the dataflow relations in a program for the guidance of test case selection.
As per a new survey by StreamSet, businesses are facing hard time keeping the data pollutants out of their big data flow.
India, June 27 -- The RBI, with a view to ensuring accuracy and integrity of data flowing from the banking system to the regulator, had recently released an approach paper on Automated Data Flow (ADF - a straight through process) from various transactional systems of the banks to RBI, to enhance data quality, ensure data integrity / accuracy and timely reporting.
Khedker, Sanyal and Karkare (computer science and engineering, IIT Bombay) have written this textbook on data flow analysis for researchers and students who need to produce performance-maximizing code, apply reverse engineering programs of verify the integrity of existing programs.
Topics covered by the publication include direct marketing regulations, subject access requests, identity theft, encryption, electronic data interchange standards, monitoring and surveillance in the workplace, international data protection, network security, infrastructure protection, cross-border data flow, outsourcing and data protection policies and audits.
This means they must take into account not only specific data points, but also the relationships between those data points, and the changes in data flow and structure over time.
Data flow, quality of service (QoS), software modifications, silicon component selection criteria and board layout are worthy of review for this next-generation PCI bus.
Recently added features include a command for designing complex surface features, automated creation of surface designs, improved data flow from the software to the company's 3-D machine control solutions, and an expanded field-data module.
An insurer must undergo a traditional gap analysis to examine what privacy data it has, how it collects it, manages it, uses it, shares it and generally each privacy data flow associated with its business, be it an internal data flow, or an external data flow.