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  2. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    Big data. Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing software. Data with many entries (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate.

  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. International Journal of Data Science and Analytics - Wikipedia

    en.wikipedia.org/wiki/International_Journal_of...

    Online archive. The International Journal of Data Science and Analytics is a peer-reviewed scientific journal covering data science. It was established in 2015 and is published by Springer Science+Business Media. The founding editor-in-chief is Longbing Cao (University of Technology Sydney). Current editor-in-chief is João Gama (INESC TEC and ...

  5. MDPI - Wikipedia

    en.wikipedia.org/wiki/MDPI

    MDPI. MDPI (Multidisciplinary Digital Publishing Institute) is a publisher of open-access scientific journals. It publishes over 390 peer-reviewed, open access journals. [2][3] MDPI is among the largest publishers in the world in terms of journal article output, [4][5] and is the largest publisher of open access articles.

  6. 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 ...

  7. Programming with Big Data in R - Wikipedia

    en.wikipedia.org/wiki/Programming_with_Big_Data_in_R

    R, C, Fortran, MPI, and ØMQ. Programming with Big Data in R (pbdR) [1] is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. [2][3] The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners ...

  8. Apache Spark - Wikipedia

    en.wikipedia.org/wiki/Apache_Spark

    Apache Spark is an open-source unified analytics engine for large-scale data processing. Spark provides an interface for programming clusters with implicit data parallelism and fault tolerance. Originally developed at the University of California, Berkeley 's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which ...

  9. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science is an interdisciplinary field [10] focused on extracting knowledge from typically large data sets and applying the knowledge and insights from that data to solve problems in a wide range of application domains. The field encompasses preparing data for analysis, formulating data science problems, analyzing data, developing data ...