Although these business intelligence data mining advanced techniques are available, you really need experts to help you. Most business applications use straightforward graphing, simple statistics and other standard data visualisation techniques.
What is Data Mining
We are drowning in data, but starving for knowledge!
Data mining is attempt to gain knowledge from masses of data.
In other words, data mining is the process of discovering meaningful correlations, patterns, and trends by sifting through large amounts of data stored in databases.
Simple Data Mining Techniques
Data mining can simply be done by visualisation of the data through simple graphing and charting e.g. scatter graphs, but can also use sophisticated pattern recognition technologies as well as statistical and mathematical techniques.
See the following simple example - the size of the circles indicates the sales volume - the colour indicates the amount of discounting (more discount - deeper the red). A pattern can be seen that stores in West have been discounting predominately!
This graph was generated using Tableau Software. Click on Graph to complete an enquiry form to gain access to a FREE trial.
The use of basic statistics in the form of regressions and multiple regressions would be the next step up from graphing.
Click here for a brief summary of the more
Advanced Data Mining Techniques
brief data mining history
Typical applications for data mining
Here are some examples of data mining applications:
- Identify buying patterns from customers
- Find associations among customer demographic characteristics
- Identify `loyal' customers
- Predict customers likely to stop using your products
- Identify fraudulent behaviour
- Characterise patient behaviour to predict office visits or non attendance
- Identify successful medication doses for different types of patient
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