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Introduction

A Data Warehouse is a database designed for decision support. It is different. Because of this is has a structure that is unique to a database. 

The conceptual architecture of a data warehouse design is generally composed of several separate systems:

• Source

• Middleware

• Storage

• User interface

• System administration

Constrains

Although many times you hear that big is better, that does not does always hold true with data warehouses. The criteria should be that the data that is needed to make a decision is available. It should not store data just for the sake of storing data.  In this regards a data warehouse should be designed according to the following rules:

• It should serve the purpose of building the warehouse 
  in the first place (why are we building a warehouse?)

• Contain the data that is relevant to the organization’s 
  interest.

• Answer all the questions that might be asked by the 
  users of the warehouse

Data Structure

Time dependent

The data within the data base has been collected over time and is time stamped

Non-volatile

The data within the data base is read only. It is only used for accessing information and never updated. 

Integrated

Contains information from many different sources. May or may not be limited by subject. 

Partitioning

Refers to the breakup of data into separate physical units the can be handled independently. Partitioning gives the user finer detail.

Examples:

• Date

• Type of symptoms

• Type of results

• By geography

• By age

• etc

Relationships between attributes in a record

Cardinality of data

Low-cardinality: values that fall within a small range of possible values

High-cardinality: values that fall within a large range of possible values

Granularity

Granularity is the major design issue in the data warehouse environment. It profoundly affects the volume of data that resides in the data warehouse and at the same time affects the type of query that can be answered. The volume of data in a warehouse is traded off against the level of detail of a query. (I-45)

In public health a very high level of detail, granularity, is desired. You must treat the individual clients.

Storage

User Interface

System Administration

• Security

  • Controls access  to data and services

• Types of attacks

  • Denial of service

• Encryption

• Ability to determine where and how data was transformed

Scalability

As the number of hits on the site increase, the number  of separate processes that the server must open, increases. This can lead to very slow response times.

Any design should allow for the expansion of the system.

Requirements 

• Grow with the number of hits

• Redundancy

• Performance Enhancement

• Load Balancing

• Security Enhancement

Hardware

• Symmetric multi-processing (SMP)

• Massively Parallel

Physical Architect

• Multi computers -> web farms

• Clustering

• Tiering

2- TIER

            Source station

            Storage station

3-TIER

            Interim transformation station

4-TIER

            Interim quality assurance station

Logical Architect

• Mini Marts

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