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Dimension_Table

One of the set of companion tables to a fact table, contains the attributes that are used to constrain and group data when performing database queries. Tables that define calendar periods, for example, are good examples of dimension tables.



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Aggregate_Data

Data that is the result of applying a process to combine data elements. The data may be taken either collectively or in summary form. For example, in a daily sales report, invoice totals and summary totals from invoices are aggregate data, whereas the individual items that are sold are atomic data.



Glossary

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Fact_Table

In a Star Schema, one large central table that typically contains one or more numerical measures or facts, such as Calls Handled, Total Time on Inbound, Dollars Sold, and so on.
A database table that consists of the measurements, metrics, or facts of a business process. It is often located at the center of a star schema, surrounded by dimension tables. Revenue tables often are categorized as fact tables.



Glossary

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Measure

In data warehousing terminology, a measure is an estimation of the magnitude of an Template loop detected: Template:Glossaryterm. For example, a measure might represent the duration of a call, or the number of agents logged in at a given moment.



Glossary

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Aggregate_Data

Data that is the result of applying a process to combine data elements. The data may be taken either collectively or in summary form. For example, in a daily sales report, invoice totals and summary totals from invoices are aggregate data, whereas the individual items that are sold are atomic data.



Glossary

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Dimension_Table

One of the set of companion tables to a fact table, contains the attributes that are used to constrain and group data when performing database queries. Tables that define calendar periods, for example, are good examples of dimension tables.



Glossary

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Star_Schema

The common term for the dimensional database model, because of its characteristic star-like structure. Dimensional modeling is a database-design technique that is used for data warehouses and data marts. Every dimensional model is composed of one large central table that is called a fact table , and a set of smaller tables that surround it and are called dimension tables . Fact tables typically contain one or more numerical measures or facts, such as Calls Handled , Total Time on Inbound , Dollars Sold , and so on. By contrast, dimension tables most often contain descriptive attributes, such as Agent Name , Queue Name , Time Period , and so on.
For an excellent resource on data warehousing, refer to http://www.dwinfocenter.org/ .



Glossary

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

iWD Data Mart Reference Guide

Welcome to the intelligent Workload Distribution 9.x Data Mart Reference Guide.

This document introduces you to the schema that make up the intelligent Workload Distribution Data Mart (iWD Data Mart) to guide you in the design and creation of reports that use the data within the iWD Data Mart.

This document is valid for the 9.x release(s) of this product.

Intended Audiences

This reference guide is intended for:

  • Reporting and business analysts who want to leverage the data that is contained in the iWD Data Mart to produce reports for business users.
  • IT administrators who would like to gain an understanding of the components that enable iWD Data Mart.

This reference guide assumes that the reader has an understanding of the following:

  • Relational database concepts.
  • Structured Query Language (SQL) for querying and mining data.
  • iWD configuration using iWD GAX Plug-in.
  • iWD Manager.
  • Data warehouse concepts—including working with star schemas, dimensions, aggregates, and measures.
  • Extraction, Transformation, and Loading (ETL) concepts.

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This page was last modified on January 31, 2018, at 08:19.