Descriptive data warehousing

Can you describe the steps in the data warehousing process?
Steps in Data Warehousing
Extraction of data – A large amount of data is gathered from various sources.
Cleaning of data – Once the data is compiled, it goes through a cleaning process.
The data is scanned for errors, and any error found is either corrected or excluded..
What are the descriptive methods of data mining?
Examples of descriptive data mining include clustering, association rule mining, and anomaly detection.
Clustering involves grouping similar objects together, while association rule mining involves identifying relationships between different items in a dataset..
What is an example of descriptive data mining?
Examples of descriptive data mining include clustering, association rule mining, and anomaly detection.
Clustering involves grouping similar objects together, while association rule mining involves identifying relationships between different items in a dataset..
Current detail data represents data of a recent nature and always has a shorter time horizon than older detail data.
Although it can be voluminous, it is almost always stored on disk to permit faster access.
Lightly summarized data represents data distilled from current detail data.

Data warehouses support business decisions by collecting, consolidating, and organizing data for reporting and analysis with tools such as online analytical

In this paper address approaches and choices to be considered when designing and implementing a data warehouse. The paper begins by contrasting data warehouse

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Descriptive data warehousing

Can you describe the steps in the data warehousing process?

What are the descriptive methods of data mining?

What is an example of descriptive data mining?