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Welcome to A-level ICT
DATABASE WAREHOUSING / DATA MINING
Organisations now store vast amounts of data in normalised form in relational databases. This data is used as a data warehouse and is mined to aid decision making.
Data Warehousing
Data Warehousing
Data Warehousing - Definition
· A large collection of archived data used for decision making.
· A large company e.g. a mail order company generates huge quantities of data stored in a consistent order to make interrogation more productive.
· Data is non-volatile and time invariant (archive data). Used to support organisational decision making.
· A huge database specifically structured for information access and reporting
Data Warehousing - Case Study
Data Warehousing - Case Study
Mail Order Company
A mail order company uses a relational database management system for storing details of orders. The company uses a data warehouse to hold details about customers and their transactions.
Benefits of Data Warehousing
Used to support organisational decision making e.g. Allows the company to find the most popular product.
Allows the company to store information about every sale.
Allows the company to see trends in buying
Allows the company to see who has bought what items and when.
Can use it to plan future changes or developments in their business.
Allows the company to use data mining.
The mail order company generates huge quantities of data stored in a consistent order to make interrogation more productive. Data is non-volatile and time invariant (archive data).
Allows the organisation to target customers with special offers (1)
Data Warehousing - Exam Tips
When writing a definition - Examiners look for 2 of these 3 keywords in your definition. (Large, Archive or Decision Making).
When describing advantages of Data Warehousing, always state the (What and Why) for two marks
e.g. Allows the company to see who has bought what items (1) and then target them with special offers. (1) (why)
Data Mining
Data Mining
Data mining is interrogating the data to find patterns in the data which is stored in the warehouse.
It is a process used by organisations to turn raw data into useful information such as patterns and trends to develop more effective marketing strategies.
Data Mining
Is interrogating the data
It is a speculative process / investigates potential patterns
Presumption is that dormant within the data are undiscovered patterns / groupings / sequences / associations.
Software uses complex algorithms to search for patterns.
Returned information can be tested for plausibility.
Data if of value can then be processed into a report to help decision making.
Could allow company to find a previously unknown relationship between regions of the country and food preferences and they can then target special promotions.
Data mining can also be described as: -
The analysis of a large amount of data in a data warehouse to provide new information?
Is a speculative process investigating potential patterns?
Involves the presumption that dormant within the data are undiscovered patterns / groupings / sequences / associations.
Software uses complex algorithms to search for patterns.
Is drilling down into the mass of data so users can understand it more / discover meaningful patterns.
Is looking for meaningful patterns in a large mass of data and presenting results in tables and graphs.
Benefits of Data Mining
The organisation could have a list of customers likely to buy a certain product, which they can then use to target with a mail shot.
Comparisons with competitors
Useful ‘what if’ results from modelling exercises
Predictions for future sales
Analysis of best sites for shops
Analysis of sales patterns
Returned information can be tested for plausibility.
Data if of value can be processed into a report to help decision making.
Data Mining - Exam Tips
Examples worth 2 marks: (What and Why) - (Why is new knowledge)
Fighting shoplifting in clothing stores – Jaeger used Data Mining to look at transactions and position of item in store (1) – they found that even with tags most items stolen were near the doors – this led to increased CCTV, more prosecutions and recovery of goods. (1)
Analyse buying patterns / Identification of customer needs – Virgin Media use Data Mining to segment and target customers (1) most likely to buy new services or upgrades. (1)
Could allow organisation to find a previously unknown relationship between regions of the country and food preferences (1) and they can then target special promotions. (1)
The difference here is that the why will refer to a new connection between the data or a new conclusion
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