Datawarehousing Tutorials -Data warehousing Concepts short tutorials

Difference Between Datawarehouse and Data warehousing

Data storage comprises of an overall architecture and procedure, whereas Data warehouse is where your information is stored in a Database in the kind of Dimension, Fact Tables, Lookup Tables, Aggregated Fact tables. Data storage is not just having an one information warehouse. Data storage is the difference of information to data, thereby enabling the job to visit its operations and operation. This work is accomplished by the staging and shift of information from information sources, making the job to access and examine data.

Dimensional Model -- an Introduction

Data warehousing is essentially what you need to do in order to create a data warehouse, and what you do with it. It is the process of creating, populating, and then querying a data warehouse and can involve a number of discrete technologies such as:

In a Dimensional Model, context of the measurements are represented in dimension tables. You can also think of the context of a measurement as the characteristics such as who, what, where, when, how of a measurement (subject ). In your business process Sales, the characteristics of the 'monthly sales number' measurement can be a Location (Where), Time (When), Product Sold (What).

The Dimension Attributes are the various columns in a dimension table. In the Location dimension, the attributes can be Location Code, State, Country, Zip code. Generally the Dimension Attributes are used in report labels, and query constraints such as where Country='USA'. The dimension attributes also contain one or more hierarchical relationships.

Before designing your data warehouse, you need to decide what this data warehouse contains. Say if you want to build a data warehouse containing monthly sales numbers across multiple store locations, across time and across products then your dimensions are:

Location
Time
Product

Each dimension table contains data for one dimension. In the above example you get all your store location information and put that into one single table called Location. Your store location data may be spanned across multiple tables in your OLTP system (unlike OLAP), but you need to de-normalize all that data into one single table.

Dimensional modeling is the design concept used by many data warehouse designers to build their data warehouse. Dimensional model is the underlying data model used by many of the commercial OLAP products available today in the market. In this model, all data is contained in two types of tables called Fact Table and Dimension Table.

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