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  2. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    Big data can be used to improve training and understanding competitors, using sport sensors. It is also possible to predict winners in a match using big data analytics. [158] Future performance of players could be predicted as well. [159] Thus, players' value and salary is determined by data collected throughout the season. [160]

  3. The Center of Applied Data Science - Wikipedia

    en.wikipedia.org/wiki/The_Center_of_Applied_Data...

    In 2016, CADS collaborated with Harvard Business School (HBS) Executive Education to launch a customised Big Data Analytics (BDA) program, with Malaysia Digital Economy Corporation (MDEC) and Human Resource Development Fund (HRDF) as stakeholders. The four-day programme took place for the first time at Hilton Kuala Lumpur from 25th to 28 April ...

  4. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    A review and critique of data mining process models in 2009 called the CRISP-DM the "de facto standard for developing data mining and knowledge discovery projects." [16] Other reviews of CRISP-DM and data mining process models include Kurgan and Musilek's 2006 review, [8] and Azevedo and Santos' 2008 comparison of CRISP-DM and SEMMA. [9]

  5. Modeling and simulation - Wikipedia

    en.wikipedia.org/wiki/Modeling_and_simulation

    As the role of big data and analytics continues to grow, the role of combined simulation of analysis is the realm of yet another professional called a simplest – in order to blend algorithmic and analytic techniques through visualizations available directly to decision makers.

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    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]

  7. Online analytical processing - Wikipedia

    en.wikipedia.org/wiki/Online_analytical_processing

    Apache Pinot is used at LinkedIn, Cisco, Uber, Slack, Stripe, DoorDash, Target, Walmart, Amazon, and Microsoft to deliver scalable real time analytics with low latency. [30] It can ingest data from offline data sources (such as Hadoop and flat files) as well as online sources (such as Kafka). Pinot is designed to scale horizontally.

  8. Behavioral analytics - Wikipedia

    en.wikipedia.org/wiki/Behavioral_analytics

    In addition to retail and political applications, behavioral analytics is also used by banks and manufacturing firms to prioritize leads generated by their websites. Behavioral analytics also allow developers to manage users in online-gaming and web applications. [5] Amongst others, IBM and Intel are creating advanced analytics solutions.

  9. Zoomdata - Wikipedia

    en.wikipedia.org/wiki/Zoomdata

    Zoomdata won the 2018 Technology Innovation Award from Dresner Advisory Services in the Big Data Analytics category. [34] Dresner Advisory Services was founded by chief research analyst Howard Dresner, who is credited with coining the term business intelligence in 1989.

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