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  2. Knowledge extraction - Wikipedia

    en.wikipedia.org/wiki/Knowledge_extraction

    Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources.The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing.

  3. Semi-structured data - Wikipedia

    en.wikipedia.org/wiki/Semi-structured_data

    Semi-structured data [1] is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.

  4. Questionnaire construction - Wikipedia

    en.wikipedia.org/wiki/Questionnaire_construction

    The types of questions (e.g.: closed, multiple-choice, open) should fit the data analysis techniques available and the goals of the survey. The manner (random or not) and location (sampling frame) for selecting respondents will determine whether the findings will be representative of the larger population .

  5. Data lake - Wikipedia

    en.wikipedia.org/wiki/Data_lake

    A data lake can include structured data from relational databases (rows and columns), semi-structured data (CSV, logs, XML, JSON), unstructured data (emails, documents, PDFs), and binary data (images, audio, video). [3] A data lake can be established on premises (within an organization's data centers) or in the cloud (using cloud services).

  6. Business intelligence - Wikipedia

    en.wikipedia.org/wiki/Business_intelligence

    Because of the way it is produced and stored, this information is either unstructured or semi-structured. The management of semi-structured data is an unsolved problem in the information technology industry. [17] According to projections from Gartner (2003), white-collar workers spend 30–40% of their time searching, finding, and assessing ...

  7. Data engineering - Wikipedia

    en.wikipedia.org/wiki/Data_engineering

    A data lake can contain structured data from relational databases, semi-structured data, unstructured data, and binary data. A data lake can be created on premises or in a cloud-based environment using the services from public cloud vendors such as Amazon , Microsoft , or Google .

  8. Data warehouse - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse

    Data Warehouse and Data mart overview, with Data Marts shown in the top right. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis and is a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...

  9. Extract, transform, load - Wikipedia

    en.wikipedia.org/wiki/Extract,_transform,_load

    Other data warehouses (or even other parts of the same data warehouse) may add new data in a historical form at regular intervals – for example, hourly. To understand this, consider a data warehouse that is required to maintain sales records of the last year. This data warehouse overwrites any data older than a year with newer data.