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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.
Azure DevOps may refer to: . Azure DevOps Server, collaboration software for software development formerly known as Team Foundation Server and Visual Studio Team System; Azure DevOps Services, cloud service for software development formerly known as Visual Studio Team Services, Visual Studio Online and Team Foundation Service Preview
Dbt enables analytics engineers to transform data in their warehouses by writing select statements, and turns these select statements into tables and views. Dbt does the transformation (T) in extract, load, transform (ELT) processes – it does not extract or load data, but is designed to be performant at transforming data already inside of a ...
Azure Data Lake is a scalable data storage and analytic service for big data analytics workloads that require developers to run massively parallel queries. Azure HDInsight [ 31 ] is a big data-relevant service that deploys Hortonworks Hadoop on Microsoft Azure and supports the creation of Hadoop clusters using Linux with Ubuntu.
Azure Linux, previously known as CBL-Mariner (in which CBL stands for Common Base Linux), [3] is a free and open-source Linux distribution that Microsoft has developed. It is the base container OS for Microsoft Azure services [ 4 ] [ 5 ] and the graphical component of WSL 2 .
Azure offers both the platform via web interface (Platform as a Service) and the hardware via virtual servers allocated to Azure accounts for data storage and processing (Infrastructure as a Service). [5] Azure Search resides within the Microsoft IaaS and PaaS suite as a service, I.E. Search as a Service (SaaS).
Data and model versioning is the base layer [21] of DVC for large files, datasets, and machine learning models. It allows the use of a standard Git workflow, but without the need to store those files in the repository. Large files, directories and ML models are replaced with small metafiles, which in turn point to
Microsoft SQL Server Analysis Services (SSAS [1]) is an online analytical processing (OLAP) and data mining tool in Microsoft SQL Server.SSAS is used as a tool by organizations to analyze and make sense of information possibly spread out across multiple databases, or in disparate tables or files.
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