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In this chapter, we will discuss the business analysis framework for the data warehouse design and architecture of a data warehouse. Business Analysis FrameworkThe business analyst get the information from the data warehouses to measure the performance and make critical adjustments in order to win over other business holders in the market. Having a data warehouse offers the following advantages −.Since a data warehouse can gather information quickly and efficiently, it can enhance business productivity.A data warehouse provides us a consistent view of customers and items, hence, it helps us manage customer relationship.A data warehouse also helps in bringing down the costs by tracking trends, patterns over a long period in a consistent and reliable manner.To design an effective and efficient data warehouse, we need to understand and analyze the business needs and construct a business analysis framework. Each person has different views regarding the design of a data warehouse. These views are as follows −.The top-down view − This view allows the selection of relevant information needed for a data warehouse.The data source view − This view presents the information being captured, stored, and managed by the operational system.The data warehouse view − This view includes the fact tables and dimension tables. It represents the information stored inside the data warehouse.The business query view − It is the view of the data from the viewpoint of the end-user.Three-Tier Data Warehouse ArchitectureGenerally a data warehouses adopts a three-tier architecture.
Following are the three tiers of the data warehouse architecture.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. These back end tools and utilities perform the Extract, Clean, Load, and refresh functions.Middle Tier − In the middle tier, we have the OLAP Server that can be implemented in either of the following ways.By Relational OLAP (ROLAP), which is an extended relational database management system. The ROLAP maps the operations on multidimensional data to standard relational operations.By Multidimensional OLAP (MOLAP) model, which directly implements the multidimensional data and operations.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.The following diagram depicts the three-tier architecture of data warehouse − Data Warehouse ModelsFrom the perspective of data warehouse architecture, we have the following data warehouse models −. Virtual Warehouse. Data mart. Enterprise WarehouseVirtual WarehouseThe view over an operational data warehouse is known as a virtual warehouse. It is easy to build a virtual warehouse. Building a virtual warehouse requires excess capacity on operational database servers. Data MartData mart contains a subset of organization-wide data.
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This subset of data is valuable to specific groups of an organization.In other words, we can claim that data marts contain data specific to a particular group. For example, the marketing data mart may contain data related to items, customers, and sales. Data marts are confined to subjects.Points to remember about data marts −.Window-based or Unix/Linux-based servers are used to implement data marts.
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