Data Mining (OCR A Level Computer Science)

Data Mining

What is Data Mining?

• Data mining is when large quantities of data are turned into useful information so that patterns can be found 

• It can be used to search for relationships and facts that are probably not immediately obvious to people

• It will extract valuable insights from large sets of data using algorithms and statistical methods

• Data mining is used in many fields, including retail, healthcare, and finance, to make informed decisions

• The diagram below shows useful business insights that can be gained from data collected by an online grocery business

How data mining can be used to generate insights

Example uses of data mining

Retail industry

• Data mining algorithms can be used to analyse purchase history and browsing behaviour to provide customised product suggestions

• Online retailers like Amazon use purchase data to suggest items for customers based on past activity

Healthcare industry

• Data from healthcare records and other sources can be analysed to predict disease outbreaks or patient admissions

• Hospitals use data mining to anticipate flu cases in the coming winter, enabling better resource allocation

Finance and banking

• Machine learning models trained on historical data can be used to identify suspicious activities among millions of transactions

• Credit card companies use data mining algorithms to flag potentially fraudulent transactions in real-time

Automotive industry

• Data collected from vehicle sensors can be used to predict when a part is likely to fail, enabling more proactive maintenance

• Manufacturers like Tesla collect data from electric cars to anticipate when a battery or other components may fail

Entertainment and media

• Data mining helps understand viewer preferences and behaviour, enabling better content recommendations

• Streaming services like Netflix use data mining to target new shows and movies to specific audiences based on their previous viewing history

Complexities in data mining

• Data mining requires knowledge of complex algorithms for data sorting, pattern recognition, and anomaly detection

• Running data mining algorithms within a company requires significant maintenance and expertise

• Companies must be careful with customer data and must ensure all mining follows the General Data Protection Regulation (GDPR)

• Specialist data engineers and data scientists are in short supply in industry