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Data Flow
In computing, dataflow is a broad concept, which has various meanings depending on the application and context. In the context of software architecture, data flow relates to stream processing or reactive programming. Software architecture Dataflow computing is a software paradigm based on the idea of representing computations as a directed graph, where nodes are computations and data flow along the edges. Dataflow can also be called stream processing or reactive programming. There have been multiple data-flow/stream processing languages of various forms (see Stream processing). Data-flow hardware (see Dataflow architecture) is an alternative to the classic von Neumann architecture. The most obvious example of data-flow programming is the subset known as reactive programming with spreadsheets. As a user enters new values, they are instantly transmitted to the next logical "actor" or formula for calculation. Distributed data flows have also been proposed as a programming ab ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computing
Computing is any goal-oriented activity requiring, benefiting from, or creating computer, computing machinery. It includes the study and experimentation of algorithmic processes, and the development of both computer hardware, hardware and software. Computing has scientific, engineering, mathematical, technological, and social aspects. Major computing disciplines include computer engineering, computer science, cybersecurity, data science, information systems, information technology, and software engineering. The term ''computing'' is also synonymous with counting and calculation, calculating. In earlier times, it was used in reference to the action performed by Mechanical computer, mechanical computing machines, and before that, to Computer (occupation), human computers. History The history of computing is longer than the history of computing hardware and includes the history of methods intended for pen and paper (or for chalk and slate) with or without the aid of tables. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gilles Kahn
Gilles Kahn (17 April 1946 – 9 February 2006) was a French computer scientist. He notably introduced Kahn process networks as a model for parallel processing and natural semantics for describing the operational semantics of programming languages. Gilles Kahn was born in Paris. He studied at the École polytechnique (X1964) and at Stanford. He became a member of the French Academy of Sciences in 1997. He was president and director-general of INRIA The National Institute for Research in Digital Science and Technology (Inria) () is a French national research institution focusing on computer science and applied mathematics. It was created under the name French Institute for Research in Comp ... from 2004 to 2006. He died in Garches. External links Page at the French academy of sciences 1946 births 2006 deaths French computer scientists Members of the French Academy of Sciences École Polytechnique alumni {{France-compu-bio-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Stream
In connection-oriented communication, a data stream is the transmission of a sequence of digitally encoded signals to convey information. Typically, the transmitted symbols are grouped into a series of packets. Data streaming has become ubiquitous. Anything transmitted over the Internet is transmitted as a data stream. Using a mobile phone to have a conversation transmits the sound as a data stream. Formal definition In a formal way, a data stream is any ordered pair ( s, \Delta ) where: # s is a sequence of tuples and # \Delta is a sequence of positive real time intervals. Content Data Stream contains different sets of data, that depend on the chosen data format. * Attributes – each attribute of the data stream represents a certain type of data, e.g. segment / data point ID, timestamp, geodata. * Timestamp attribute helps to identify when an event occurred. * Subject ID is an encoded-by-algorithm ID, that has been extracted out of a cookie. * Raw Data in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data-flow Analysis
Data-flow analysis is a technique for gathering information about the possible set of values calculated at various points in a computer program. It forms the foundation for a wide variety of compiler optimizations and program verification techniques. A program's control-flow graph (CFG) is used to determine those parts of a program to which a particular value assigned to a variable might propagate. The information gathered is often used by compilers when optimizing compiler, optimizing a program. A canonical example of a data-flow analysis is reaching definitions. Other commonly used data-flow analyses include live variable analysis, available expressions, constant propagation, and very busy expressions, each serving a distinct purpose in compiler optimization passes. A simple way to perform data-flow analysis of programs is to set up data-flow equations for each node (computer science), node of the control-flow graph and solve them by repeatedly calculating the output from the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data-flow Diagram
A data-flow diagram is a way of representing a flow of data through a process or a system (usually an information system). The DFD also provides information about the outputs and inputs of each entity and the process itself. A data-flow diagram has no control are no decision rules and no loops. Specific operations based on the data can be represented by a flowchart. There are several notations for displaying data-flow diagrams. The notation presented above was described in 1979 by Tom DeMarco as part of structured analysis. For each data flow, at least one of the endpoints (source and / or destination) must exist in a process. The refined representation of a process can be done in another data-flow diagram, which subdivides this process into sub-processes. The data-flow diagram is a tool that is part of structured analysis, data modeling and threat modeling. When using UML, the activity diagram typically takes over the role of the data-flow diagram. A special form of data-fl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Complex Event Processing
Event processing is a method of tracking and analyzing (processing) streams of information (data) about things that happen (events), and deriving a conclusion from them. Complex event processing (CEP) consists of a set of concepts and techniques developed in the early 1990s for processing real-time events and extracting information from event streams as they arrive. The goal of complex event processing is to identify meaningful events (such as opportunities or threats) in real-time situations and respond to them as quickly as possible. These events may be happening across the various layers of an organization as sales leads, orders or customer service calls. Or, they may be news items, text messages, social media posts, business processes (such as supply chain), traffic reports, weather reports, or other kinds of data. An event may also be defined as a "change of state," when a measurement exceeds a predefined threshold of time, temperature, or other value. Analysts have suggest ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Communicating Sequential Processes
In computer science, communicating sequential processes (CSP) is a formal language for describing patterns of interaction in concurrent systems. It is a member of the family of mathematical theories of concurrency known as process algebras, or process calculi, based on message passing via channels. CSP was highly influential in the design of the occam programming language and also influenced the design of programming languages such as Limbo, RaftLib, Erlang (programming language), Erlang, Go (programming language), Go, Crystal (programming language), Crystal, and Clojure's core.async. CSP was first described by Tony Hoare in a 1978 article, and has since evolved substantially. CSP has been practically applied in industry as a tool for formal specification, specifying and verifying the concurrent aspects of a variety of different systems, such as the T9000 Transputer, as well as a secure e-commerce system. The theory of CSP itself is also still the subject of active research, in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Binary Modular Dataflow Machine
Binary Modular Dataflow Machine (BMDFM) is a software package that enables running an application in parallel on shared memory symmetric multiprocessing (SMP) computers using the multiple processors to speed up the execution of single applications. BMDFM automatically identifies and exploits parallelism due to the static and mainly ''dynamic scheduling'' of the dataflow instruction sequences derived from the formerly sequential program. The BMDFM dynamic scheduling subsystem performs a symmetric multiprocessing (SMP) emulation of a ''tagged-token dataflow machine'' to provide the transparent dataflow semantics for the applications. No directives for parallel execution are needed. Background Current parallel shared memory SMPs are complex machines, where a large number of architectural aspects must be addressed simultaneously to achieve high performance. Recent commodity SMP machines for technical computing can have many tightly coupled cores (good examples are SMP machines bas ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Cloud Dataflow
Google Cloud Dataflow is a fully managed service for executing Apache Beam pipelines within the Google Cloud Platform ecosystem. Dataflow provides a fully managed service for executing Apache Beam pipelines, offering features like autoscaling, dynamic work rebalancing, and a managed execution environment. Dataflow is suitable for large-scale, continuous data processing jobs, and is one of the major components of Google's big data architecture on the Google Cloud Platform. History Google Cloud Dataflow was announced in June, 2014 and released to the general public as an open beta in April, 2015. In January, 2016 Google donated the underlying SDK, the implementation of a local runner, and a set of IOs ( data connectors) to access Google Cloud Platform data services to the Apache Software Foundation. The donated code formed the original basis for Apache Beam. In August 2022, there was an incident where user timers were broken for certain Dataflow streaming pipelines in multiple re ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Microsoft Dataverse
Microsoft Power Platform is a collection of low-code development tools that allows users to build custom business applications, automate workflows, and analyze data. It also offers integration with GitHub, Microsoft Azure, Microsoft Dynamics 365, and Microsoft Teams, amongst other Microsoft and third-party applications. Microsoft Power Platform enables users to streamline processes, gain insights from their data, and build custom solutions to meet their business needs. It is designed to be accessible to users with varying levels of technical expertise, making it easier for organizations to create custom applications and automate workflows. Microsoft developed the Power Fx low-code programming language for expressing logic across the Power Platform. Products The Power Platform family of products includes: * Power BI, a business analytics tool for visualizing data through various charts, graphs, and dashboards. It competes with tools like Tableau, Spotfire or Qlikview. * Power ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Cleansing
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data. Data cleansing can be performed interactively using data wrangling tools, or through batch processing often via scripts or a data quality firewall. After cleansing, a data set should be consistent with other similar data sets in the system. The inconsistencies detected or removed may have been originally caused by user entry errors, by corruption in transmission or storage, or by different data dictionary definitions of similar entities in different stores. Data cleaning differs from data validation in that validation almost invariably means data is rejected from the system at entry and is performed at the time of entry, rather than on batches of data. The actual process ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Power Query
Power Query is an ETL tool created by Microsoft for data extraction, loading and transformation, and is used to retrieve data from sources, process it, and load them into one or more target systems. Power Query is available in several variations within the Microsoft Power Platform, and is used for business intelligence on fully or partially self-service platforms. It is found in software such as Excel, Power BI, Analysis Services, Dataverse, Power Apps, Azure Data Factory, SSIS, Dynamics 365, and in cloud services such as Microsoft Dataflows, including Power BI Dataflow used with the online Power BI Service or the somewhat more generic version of Microsoft Dataflow used with Power Automate. ETL is closely related to data modeling, and for transformation, Power Query can be used to develop a logical data model in those cases where the data does not already have one, or where there is a need to further develop the data model. History Power Query was first announced in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
