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  2. CircleCI - Wikipedia

    en.wikipedia.org/wiki/CircleCI

    CircleCI is a continuous integration (CI) and continuous delivery (CD) platform that can be used to implement DevOps practices. [2] The company was founded in September 2011 and has raised $315 million in venture capital funding as of 2021, at a valuation of $1.7 billion. [1] CircleCI is one of the world's most popular CI/CD platforms. [3]

  3. Big data maturity model - Wikipedia

    en.wikipedia.org/wiki/Big_Data_Maturity_Model

    The TDWI big data maturity model is a model in the current big data maturity area and therefore consists of a significant body of knowledge. [6] Maturity stages. The different stages of maturity in the TDWI BDMM can be summarized as follows: Stage 1: Nascent. The nascent stage as a pre–big data environment. During this stage:

  4. Data-driven model - Wikipedia

    en.wikipedia.org/wiki/Data-driven_model

    Data-driven models encompass a wide range of techniques and methodologies that aim to intelligently process and analyse large datasets. Examples include fuzzy logic, fuzzy and rough sets for handling uncertainty, [3] neural networks for approximating functions, [4] global optimization and evolutionary computing, [5] statistical learning theory, [6] and Bayesian methods. [7]

  5. Data modeling - Wikipedia

    en.wikipedia.org/wiki/Data_modeling

    The data modeling process. The figure illustrates the way data models are developed and used today . A conceptual data model is developed based on the data requirements for the application that is being developed, perhaps in the context of an activity model. The data model will normally consist of entity types, attributes, relationships ...

  6. DataOps - Wikipedia

    en.wikipedia.org/wiki/Dataops

    DataOps is a set of practices, processes and technologies that combines an integrated and process-oriented perspective on data with automation and methods from agile software engineering to improve quality, speed, and collaboration and promote a culture of continuous improvement in the area of data analytics. [1]

  7. In-database processing - Wikipedia

    en.wikipedia.org/wiki/In-database_processing

    In-database processing, sometimes referred to as in-database analytics, refers to the integration of data analytics into data warehousing functionality. Today, many large databases, such as those used for credit card fraud detection and investment bank risk management, use this technology because it provides significant performance improvements over traditional methods.

  8. Poll: Majority of Americans support Trump's plan to declare ...

    www.aol.com/poll-majority-americans-support...

    (The Center Square) – A majority of Americans support President-elect Donald Trump's plan to declare a national emergency over the border crisis, according to a new poll. Declaring such an ...

  9. KNIME - Wikipedia

    en.wikipedia.org/wiki/KNIME

    KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.