Database Management System

Database Management System
The research that I have done for this individual assignment where I need to provide a brief explanation of olap, Data Warehouse and Data Mart, Three-tier architecture and asp was through a research online. I found that most of these acronyms for computer terminology are hard to find when the meanings that apply to your subject or acronym you are un-aware of it. In conclusion all the above words are related one to each other.The research that I have done for this individual assignment where I need to provide a brief explanation of olap, Data Warehouse and Data Mart, Three-tier architecture and asp was through a research online. I found that most of these acronyms for computer terminology are hard to find when the meanings that apply to your subject or acronym you are un-aware of it. In conclusion all the above words are related one to each other.

Let me start this paper providing a shot briefing about how hard was for me finding most of the explanation of these four terminologies that I will be explaining below.

olap is the first word that I will define in my paper. olap is an acronym for On-Line Analytical Processing. It is an approach to quickly providing the answer to complex database queries. Is used in today business for reporting sales, marketing, management reporting, data mining and similar areas.

The main reason of using olap to answer queries is speed. Relational databases store entities in discrete tables if they have been properly normalized. This structure is good for operational databases but for complex multi-table queries is comparatively slow. A better model for querying but worse for operational use is the dimensional database.

olap take a snapshot of a relational database and restructures it into dimensional data. The queries can ten be run against this. It has been claimed that for complex queries olap can produce a result in around 0.1% of the time for the same query on relational data.

For example a set of customers can be grouped by city, by district or by country; so with 50 cities, 8 districts and two countries there are three hierarchical levels with 60 members. These customers can be considered in relation to products; if there are 250 products with 20 categories, three families and three departments then there are 276 product members. With just these two dimensions there are 16,560 possible aggregations. As the data considered increases the number of aggregations can quickly total tens of millions or more.

The above example from Webopedia.com give us a better picture how many more aggregations are add without notice it. Thanks to OnLine Analitical Processing minized the time to a result in around 0.1% of the time for the same query on a relational data.

The second terminology that I research was Data Warehouse and Data Mart. Data Warehouse and Data Mart is coorporate memory. Let?s take this other terminology and break it in two part; one Data Warehouse and the second one Data Mart. Starting by Data Warehouse, academics will say it is a subject oriented, point-in-time, inqury only collection of operational data. And what this mean? Easy. Typical relational databses are designed for On-Line Transactional Processing (oltp) and do not meet the requirements for effective On-Line Analytical Processing (olap). As a result data warehouses are designed differently that traditional relational databases.

Now that we just explained the first part of this second terminoly lets take the second part; Data Mart. Data Mart is a miniature data warehouse; in others words is just on segment of the organization. A good example is the one that Microsoft Developer Network provide us in his page: A large service organization may treat regional operating centers as individual business units, each with its own data mart that contributes to the master warehouse.

Data marts are sometime designed as complete individual data warehouses and contribute to overall organization as a member of a distributed data warehouse. In other designs, data marts receive data from a master data warehouse through periodic updates, in which case the data mart functionality is often limited to presentation services for clients.

The third terminology that I need to explain for this week paper is Three-tier architecture. A Three-tier architecture is relatively new because start in the mid to late 90?s. The purpose of this is to separate the user interface, business processing and the database access.
Three-tier architecture is used when an effective distribute client/server design is needed that provides increased flexibility, maintainability, reusability and scalability, while hiding the complexity of distributed processing from the user. These characteristics have made three layer architectures a popular choice for internet application and net-centric information systems. Some of you might be asking why not everyone is using it. Well the reason that not everyone is using it is because Three-tier architectures increased complexity and decreased performance which is not good because performance is one of the most important features.

Database Management System 9.5 of 10 on the basis of 1746 Review.