Saturday, March 17, 2012

Data Warehousing Concepts - Just What Are The Simplest Means To Make Use Of Data Warehouses To Aid Your Business Intelligence?

By Daniel Turbin


Data warehousing concepts are definitions and terms within the area of data warehousing, which entails the storage of data-more especially, computer data, network data. Amongst the concepts most vital to data warehousing is "data warehouses." Data warehouses (DW) are massive amounts of data extracted from multiple sources and put together to help influence future business decisions. DWs consist of data marts, places where data from diverse sources are brought together. Extracted data are set in a data mart before it is assimilated. Another data warehousing concept, business intelligence (BI) or "decision support system" (DSS), refers to analysis of business data, such as consumer sales, percentage of sales progress, determination of high-demand products, what positive savings campaigns consumers respond to most, the time of the month and year where customers invest the most money (and time in which they spend the least), easy computer applications that let customers to pay and purchase company products, etc.

Data modelling

Other concepts of data warehousing consist of the following terms:

Star schema

Snowflake schema

Conceptual data model

Logical data model

External data model

Dimensional data model

Data mining

Staging area

Operational Data Store

Multidimensional Analysis

On-Line Analytical Processing (OLAP)

Multi-dimensional database

Hypercube

OLAP tools

Data mining is another important concept regarding data warehousing. Data mining is the process in which data are extracted from several sources and a pattern is established by the data that provide a piece of knowledge for the one who recognizes the pattern. A nice example of a pattern would be someone who observes that no products are sold on the second and fourth weeks of every month. Maybe products are not sold in those 2 weeks because of little income: working people have already utilized their checks to pay bills, hence they have little money left over.

Another illustration pertains to the pattern that no one buys portable DVD players any longer. This pattern reveals that folks no more buy the portable players since 1) computers include DVD players and 2) websites like Amazon Instant Video offer you video rentals as well as plays on Internet stream, rather than DVD play. Patterns like book sales decreasing or restaurants sales decreasing over a three-month period may show that the bookstore or restaurant is executing something wrong. The exact issue may be related to speculation to some degree, but the pattern is clear: sales are falling.

Usually, customer savings, sales, rebates, and special offers like "buy one, get one free" are what shops and owners use so as to increase sales in a time of financial decline. Data architecture (DA) pertains to models or policies that govern how data is gathered, stored, arranged, and used for business purposes. DA answers questions such as "Why are data bits arranged as they are?" and "What types of data are gathered? What does the business expect from an examination of the various data that exist in the system?"

Data warehousing takes place when data are extracted from business applications (DW), put into one place (data mart), and utilized to influence company policy and business actions by turning the information into physical data models-charts, graphs, and also tables that can be seen by employees and plainly understood. The extracted info then reformatted, reorganized, summed up, and provided with other extracted data. Once the data has been through a process of refinement, it is then all set for reports, presentations (Powerpoint, for example) by using charts, graphs, and other business documents.



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