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  2. Data quality - Wikipedia

    en.wikipedia.org/wiki/Data_quality

    A number of vendors make tools for analyzing and repairing poor quality data in situ, service providers can clean the data on a contract basis and consultants can advise on fixing processes or systems to avoid data quality problems in the first place. Most data quality tools offer a series of tools for improving data, which may include some or ...

  3. Big data - Wikipedia

    en.wikipedia.org/wiki/Big_data

    The term big data has been in use since the 1990s, with some giving credit to John Mashey for popularizing the term. [22] [23] Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time.

  4. Big data maturity model - Wikipedia

    en.wikipedia.org/wiki/Big_Data_Maturity_Model

    They provide tools that assist organizations to define goals around their big data program and to communicate their big data vision to the entire organization. BDMMs also provide a methodology to measure and monitor the state of a company's big data capability, the effort required to complete their current stage or phase of maturity and to ...

  5. Precisely (company) - Wikipedia

    en.wikipedia.org/wiki/Precisely_(company)

    Precisely Holdings, LLC, doing business as Precisely, is a software company specializing in data integrity tools, and also providing big data, high-speed sorting, ETL, data integration, data quality, data enrichment, and location intelligence offerings.

  6. Data management - Wikipedia

    en.wikipedia.org/wiki/Data_management

    While there are numerous analysis tools in the market, Big Data analytics is the most common and advanced technology that has led to the following hypothesis: Data analytic tools used to analyze data collected from numerous data sources determine the quality and reliability of data analysis.

  7. 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]

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