A data warehouse can be considered as a storage area where interest specific or relevant data is stored irrespective of the source. What actually is required to create a data warehouse can be considered as Dataware housing Data warehousing merges data from multiple sources into an easy and complete form.
What are fact tables and dimension tables?
As mentioned, data in a warehouse comes from the transactions. Fact table in a data warehouse consists of facts and/or measures. The nature of data in a fact table is usually numerical.
On the other hand, dimension table in a data warehouse contains fields used to describe the data in fact tables. A dimension table can provide additional and descriptive information (dimension) of the field of a fact table.
e.g. If I want to know the number of resources used for a task, my fact table will store the actual measure (of resources) while my Dimension table will store the task and resource details.
Hence, the relation between a fact and dimension table is one to many.
What is ETL process in data warehousing?
ETL stands for Extraction, transformation and loading. That means extracting data from different sources such as flat files, databases or XML data, transforming this data depending on the application’s need and loads this data into data warehouse.
Explain the difference between data mining and data warehousing?
Data mining is a method for comparing large amounts of data for the purpose of finding patterns.Data mining is normally used for models and forecasting. Data mining is the process of correlations, patterns by shifting through large data repositories using pattern recognition techniques.
Data warehousing is the central repository for the data of several business systems in an enterprise. Data from various resources extracted and organized in the data warehouse selectively for analysis and accessibility.
What is an OLTP system and OLAP system?
OLTP stands for OnLine Transaction Processing.Application
that supports and manges transactions which involve high volumes of data are supported by OLTP system. OLTP is based on client-server architecture and supports transactions across networks.
OLAP stands for OnLine Analytical Processing. Business data analysis and complex calculations on low volumes of data are performed by OLAP. An insight of data coming from various resources can be gained by a user with the support of OLAP.
What are cubes?
Multi dimensional data is logically represented by Cubes in data warehousing. The dimension and the data are represented by the edge and the body of the cube respectively. OLAP environments view the data in the form of hierarchical cube. A cube typically includes the aggregations that are needed for business intelligence queries.