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  2. Microsoft Azure - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Azure

    Azure HDInsight [30] 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 Stream Analytics is a Serverless scalable event-processing engine that enables users to develop and run real-time analytics on multiple streams of data from sources ...

  3. Azure Data Explorer - Wikipedia

    en.wikipedia.org/wiki/Azure_Data_Explorer

    Azure Data Explorer is a distributed database running on a cluster of compute nodes in Microsoft Azure. It is based on relational database management systems (RDBMS), supporting entities such as databases, tables, functions, and columns. It supports complex analytics query operators, such as calculated columns, searching and filtering on rows ...

  4. Databricks - Wikipedia

    en.wikipedia.org/wiki/Databricks

    Website. databricks.com. Databricks, Inc. is a global data, analytics and artificial intelligence company founded by the original creators of Apache Spark. [3] The company provides a cloud-based platform to help enterprises build, scale, and govern data and AI, including generative AI and other machine learning models. [4]

  5. Mark Russinovich - Wikipedia

    en.wikipedia.org/wiki/Mark_Russinovich

    Website. markrussinovich.com. Mark Eugene Russinovich (born December 22, 1966) is a Spanish-born American software engineer and author who serves as CTO of Microsoft Azure. He was a cofounder of software producers Winternals before Microsoft acquired it in 2006.

  6. Software engineering - Wikipedia

    en.wikipedia.org/wiki/Software_engineering

    Software engineering is an engineering approach to software development. [1][2][3] A practitioner, called a software engineer, applies the engineering design process to develop software. The terms programmer and coder overlap software engineer, but they imply only the construction aspect of typical software engineer workload.

  7. Data engineering - Wikipedia

    en.wikipedia.org/wiki/Data_engineering

    Data engineering. Data engineering refers to the building of systems to enable the collection and usage of data. This data is usually used to enable subsequent analysis and data science, which often involves machine learning. [1][2] Making the data usable usually involves substantial compute and storage, as well as data processing.

  8. Application lifecycle management - Wikipedia

    en.wikipedia.org/wiki/Application_lifecycle...

    Modern software development processes are not restricted to the discrete ALM/SDLC steps managed by different teams using multiple tools from different locations. [citation needed] Real-time collaboration, access to the centralized data repository, cross-tool and cross-project visibility, better project monitoring and reporting are the key to developing quality software in less time.

  9. Site reliability engineering - Wikipedia

    en.wikipedia.org/wiki/Site_reliability_engineering

    Site reliability engineering. Site reliability engineering (SRE) is a set of principles and practices that applies aspects of software engineering to IT infrastructure and operations. [1] SRE aims to create highly reliable and scalable IT systems. Although they are closely related, SRE is slightly different from DevOps. [2][3][4]

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