Overview of Descriptive Statistics - Teradata Warehouse Miner

In-Database Analytic Functions User Guide

Product
Teradata Warehouse Miner
Release Number
5.4.2
Published
October 2016
Language
English (United States)
Last Update
2018-05-04
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B035-2306
lifecycle
previous
Product Category
Teradata® Warehouse Miner
Descriptive Statistics provides a variety of functions to statistically analyze and explore a Teradata database. Descriptive statistical analysis is valuable for several reasons:
  • It can provide business insight in its own right
  • It uncovers data quality issues, which, if not corrected or compensated for, would jeopardize the accuracy of any analytic models that are based on the data
  • It isolates the data that should be used in building analytic models. For example, outlying values should sometimes be excluded from a model; in other cases, these values might be required to solve a particular business problem.
  • Some statistical processes used in analytic modeling require a certain type of distribution of data. Descriptive statistical analysis can help determine the suitability of various data elements for model input and can suggest transformations that may be required for these data elements.