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  2. Data validation - Wikipedia

    en.wikipedia.org/wiki/Data_validation

    Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]

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

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

    The validation data set functions as a hybrid: it is training data used for testing, but neither as part of the low-level training nor as part of the final testing. The basic process of using a validation data set for model selection (as part of training data set, validation data set, and test data set) is: [10] [14]

  4. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    However, in data warehouses, which do not permit interactive updates and which are specialized for fast query on large data volumes, certain DBMSs use an internal 6NF representation – known as a columnar data store. In situations where the number of unique values of a column is far less than the number of rows in the table, column-oriented ...

  5. Help:Table/Advanced - Wikipedia

    en.wikipedia.org/wiki/Help:Table/Advanced

    Tables will show the "[hide]" / "[show]" controls in the first row of the table (whether or not it is a header row), unless a table caption is present.(see § Tables with captions) Example with a header row

  6. Help:Advanced table formatting - Wikipedia

    en.wikipedia.org/wiki/Help:Advanced_table_formatting

    For each table, insert an alpha-prefix on each column (making each row-token "|-" to sort as column zero, like prefix "Row124col00"), then sort into a new file, and then de-prefix the column entries. Again, bear in mind, the tedious hand-editing of items in each row is often faster than the potential delay of automated edits gone awry.

  7. Statistical model validation - Wikipedia

    en.wikipedia.org/wiki/Statistical_model_validation

    In statistics, model validation is the task of evaluating whether a chosen statistical model is appropriate or not. Oftentimes in statistical inference, inferences from models that appear to fit their data may be flukes, resulting in a misunderstanding by researchers of the actual relevance of their model.

  8. Referential integrity - Wikipedia

    en.wikipedia.org/wiki/Referential_integrity

    A table (called the referencing table) can refer to a column (or a group of columns) in another table (the referenced table) by using a foreign key. The referenced column(s) in the referenced table must be under a unique constraint, such as a primary key. Also, self-references are possible (not fully implemented in MS SQL Server though [5]).

  9. Data validation and reconciliation - Wikipedia

    en.wikipedia.org/wiki/Data_validation_and...

    Data reconciliation is a technique that targets at correcting measurement errors that are due to measurement noise, i.e. random errors.From a statistical point of view the main assumption is that no systematic errors exist in the set of measurements, since they may bias the reconciliation results and reduce the robustness of the reconciliation.