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  2. Feature engineering - Wikipedia

    en.wikipedia.org/wiki/Feature_engineering

    On the other hand, it enables non-experts, who are not familiar with data science, to quickly extract value from their data with a little effort, time, and cost. [22] getML community is an open source tool for automated feature engineering on time series and relational data. [23] [24] It is implemented in C/C++ with a Python interface. [24]

  3. Anchor modeling - Wikipedia

    en.wikipedia.org/wiki/Anchor_Modeling

    Unlike the star schema (dimensional modelling) and the classical relational model (3NF), data vault and anchor modeling are well-suited for capturing changes that occur when a source system is changed or added, but are considered advanced techniques which require experienced data architects. [2] Both data vaults and anchor models are entity ...

  4. Data build tool - Wikipedia

    en.wikipedia.org/wiki/Data_build_tool

    It started at RJMetrics in 2016 as a solution to add basic transformation capabilities to Stitch (acquired by Talend in 2018). [3] The earliest versions of dbt allowed analysts to contribute to the data transformation process following the best practices of software engineering. [4] From the beginning, dbt was open source. [5]

  5. Data transformation (computing) - Wikipedia

    en.wikipedia.org/wiki/Data_transformation...

    Traditionally, data transformation has been a bulk or batch process, [6] whereby developers write code or implement transformation rules in a data integration tool, and then execute that code or those rules on large volumes of data. [7] This process can follow the linear set of steps as described in the data transformation process above.

  6. Data wrangling - Wikipedia

    en.wikipedia.org/wiki/Data_wrangling

    Data wrangling, sometimes referred to as data munging, is the process of transforming and mapping data from one "raw" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics. The goal of data wrangling is to assure quality and useful data.

  7. Intelligent transformation - Wikipedia

    en.wikipedia.org/wiki/Intelligent_transformation

    Intelligent transformation is the process of deriving better business and societal outcomes by leveraging smart devices, big data, artificial intelligence, and cloud technologies. Intelligent transformation can facilitate firms in gaining recognition from external investors, thereby enhancing their market image and attracting larger consumers ...

  8. Andy Cohen Reveals the Most Annoying Part of Co-Hosting ... - AOL

    www.aol.com/andy-cohen-reveals-most-annoying...

    Andy Cohen is spilling the tea on what it's like working with longtime friend and colleague Anderson Cooper. Before SiriusXM's 10th Annual Radio Andy Holiday Hangout (which he co-hosts with Amy ...

  9. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1] Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science ...