What is a Data Warehouse? (Research Paper Sample)

What Is a Data Warehouse?
A data warehouse is a database designed to enable business intelligence activities: it exists to help users understand and enhance their organization's performance.Data warehouses separate analysis workload from transaction workload and enable an organization to consolidate data from several sources.With a data warehouse you separate analysis workload from transaction workload. Thus data warehouses are very much read-oriented systems. They have a far higher amount of data reading versus writing and updating. This enables far better analytical performance and avoids impacting your transaction systems.
Users of the data warehouse perform data analyses that are often time-related. Examples include consolidation of last year's sales figures, inventory analysis, and profit by product and by customer.
characteristics and functioning of Data Warehousing :
1). Subject Oriented:
Data warehouses are designed to help you analyze data. For example, to learn more about your company's sales data, you can build a warehouse that concentrates on sales.This ability to define a data warehouse by subject matter, sales in this case, makes the data warehouse subject oriented.
2. Integrated:
Integration is closely related to subject orientation. Data warehouses must put data from disparate sources into a consistent format.They must resolve such problems as naming conflicts and inconsistencies among units of measure. When they achieve this, they are said to be integrated.
3). Integrated:
Integration is closely related to subject orientation. Data warehouses must put data from disparate sources into a consistent format. They must resolve such problems as naming conflicts and inconsistencies among units of measure.
4). Nonvolatile:
Nonvolatile means that, once entered into the warehouse, data should not change. This is logical because the purpose of a warehouse is to enable you to analyze what has occurred.
5). Time Variant:
In order to discover trends in business, analysts need large amounts of data.A data warehouse's focus on change over time is what is meant by the term time variant.
Data Warehousing - Architecture.
1). Three - Tier Data Warehouse Architecture : Generally a data warehouses adopts a three-tier architecture. Following are the three tiers of the data warehouse architecture.The three tiers of the data:
Top-Tier - This tier is the front-end client layer. This layer holds the query tools and reporting tools, analysis tools and data mining tools.
Middle Tier - In the middle tier, we have the OLAP Server that can be implemented in either of the by Relational OLAP or by Multidimensional OLAP.
Bottom Tier - The bottom tier of the architecture is the data warehouse database server. It is the relational database system. We use the back end tools and utilities to feed data into the bottom tier.
2). Data Warehouse Models : From the perspective of