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Data Mining and Data Warehouse

posted Nov 29, 2010, 1:40 AM by Unknown user

Each of the following items relates to (a) Data Warehouses and (b) Data Mining.

1.        Describe what each is.

2.       Outline the benefits that can be gained by organisations that keep these

3.       Explain with examples how each could potentially be abused

4.       Using the internet, identify two companies that do each (for a total of four companies) and justify (with examples) the use of such methods for each company.


1.       Data Warehouses is a database that collects information from different data sources which is collected and placed together in order to develop relationships. It is a storage area of raw data that can be analysed to assist organisations to make decisions. Data Mining is a process that looks for relationships and patterns in the data stored in a database. It sorts data and turns up interesting and useful connections.


2.       Data Warehouses will allow organisations to draw data from several sources in order to develop an accurate reading (analysis of situation) before a decision is made. It gives access to large amounts of information. Providing a broader idea of the context of any decision to be made, and moreover allows these ideas to be simplified such that they can be analysed simply. Data Mining uses this concept to provide organisations to look into possible future predictions and relationships of how it works and possible improvements which could be made.


3.       Data Warehouses and Mining will raise issues of privacy and ownership of data. Data Warehousing may develop into a system which sources data which is completely irrelevant to the organisation's purpose and invades another's privacy. Intern, the copyright of some data may also be breached. How a system conducts itself whilst developing data warehouses is hence a key issue. For example, authorities how need to know much of this data, but others with malicious intents may use this data for purposes other than that related to the organisation worked for. Data Mining may again lead to relationships which deviate from the original purpose of the organisation. It can lead to the development or holding of personal data such as phone or credit card no. which may invade one's privacy. For example, a banker who holds their customer data may mine through personal data such as address and phone number instead of customer ID and their financial situation. Furthermore, if a script of a play was to be mined from a data warehouse of an acting institution which is yet to be performed, data ownership would become an issue raised of whether the organisation can use it.


4.       SMH- SMH needs to perform data warehousing in order to gather and publish all its articles on the internet as well as the daily papers. Not only that, it like all other companies needs to research optimal timings to advertise and campaign for the purchase of their newspaper product. It is essential for this to occur in order to optimise customer purchase of the newspaper and hence to entire organisation's livelihood. For example, TV advertisements for the newspaper which include a special toy of a sought will require a data warehouse as well as the data mining technique in order to discover when the most suitable time for displaying children/family related advertisements with optimal target audience viewing is possible.


Google- Google continuously needs to discover ways to improve its services through continual market research, which like SMH can be performed through utilising a data mining which identifies peak hours of use as well as relationships between certain periods of time and particular searches. From this, the organisation may have the ability to develop and improve its current services from this mined information. Furthermore, Google maps requires a constant feed of traffic flow data updates from which the product itself can be made most accurate. Accumulating such vast amounts of data from all over the world considering the traffic of all the cities which use this service also shows the need data warehousing as a technique to develop this service.


McDonalds- McDonalds, like SMH, also needs to find ideal times to run particular commercials as well as the placement of billboards and posters. Through the use of a data warehouse, accurate data which converges several statistics will not provide a guessing method of timing particular advertisements but a concrete and justifiable timing to all TV and Radio ads. For example, a Happy Meal TV advertisement would most likely be useful between the hours of 7-8am as well as 3-5pm, which is where most children watch the TV. The placement of billboards can also be influenced by collecting data concerning the number of people who pass a certain road as well as the timings of these. This can be used by McDonalds via the technique data mining as a method of understanding why a breakfast deal-promoting poster should be placed in front of a highway; as over 10,000 people pass through between 6-7am on the way to the city (i.e. Work) which is ideal for such promotion.


Apple- As a result of its advancement as an expansive global selling company, Apple is likely to have large amounts of data concerning its product development, feedback as well as any issues with its products. In order to develop a clear method of analysing this data into meaningful information, data mining can be used in order to more accurately developing feedback and issue consultations. In order to continue discovering world-first breakthroughs in technology globally, data warehousing is necessary to keep the organisation up to date. Once again, developing accurate market research through data warehousing in order to confirm advertising logistics is also possible by researching the movements of the followers of technology.