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In automation production technology the actions performed by an automated process are executed by a program of instructions which is run during a work cycle. To execute work cycle programs, an automated system should be available to execute these advanced functions.
Azure DevOps Server, formerly known as Team Foundation Server (TFS) and Visual Studio Team System (VSTS), is a Microsoft product that provides version control (either with Team Foundation Version Control (TFVC) or Git), reporting, requirements management, project management (for both agile software development and waterfall teams), automated builds, testing and release management capabilities.
Microsoft Azure uses large-scale virtualization at Microsoft data centers worldwide and offers more than 600 services. [11] Microsoft Azure offers a service level agreement (SLA) that guarantees 99.9% availability for applications and data hosted on its platform, subject to specific terms and conditions outlined in the SLA documentation.
In Microsoft Windows applications programming, OLE Automation (later renamed to simply Automation [1] [2]) is an inter-process communication mechanism created by Microsoft.It is based on a subset of Component Object Model (COM) that was intended for use by scripting languages – originally Visual Basic – but now is used by several languages on Windows.
Application-release automation (ARA) refers to the process of packaging and deploying an application or update of an application from development, across various environments, and ultimately to production. [1] ARA solutions must combine the capabilities of deployment automation, environment management and modeling, and release coordination. [2]
[citation needed] A good ETL tool must be able to communicate with the many different relational databases and read the various file formats used throughout an organization. ETL tools have started to migrate into enterprise application integration , or even enterprise service bus , systems that now cover much more than just the extraction ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]
Sample (Random): Specifies whether the product supports selecting a random sample of rows from the table/file (population). Sample (Monetary unit): Specifies whether the product supports selecting a monetary unit sample of rows from the table/field (population). This is also known as dollar-unit sampling (when values are in U.S. currency).