Data analysis is a very effective way of improving business performance. By compiling, understanding and modelling data, you can draw conclusions that inform strategic decision-making. The four main types of data analysis are:
1. Descriptive analysis.
Descriptive analysis compiles data to support businesses in understanding what happened but does not necessarily explain why. It is useful to include descriptive analysis in any modelling activity but not to rely on it in isolation.
2. Diagnostic analysis.
Diagnostic analysis involves measuring historical data against other information sources to understand the impact of outside influences. It is essential that trusted sources are used; otherwise, false judgements may be drawn.
3. Predictive analysis.
The main reason why businesses employ the services of a data analysis company such as https://shepper.com/ is to perform predictive analysis, helping them to understand what outcomes may be possible based on past performance modelled against potential actions.
4. Prescriptive analysis.
Prescriptive analysis is used to eliminate problems or benefit from trends by using data to identify opportunities to exploit. It relies upon accurate and timely data collection, careful analysis of historical data and a strong understanding of any relevant data sources that may impact planned outcomes.
In conclusion
Depending upon what outcome you wish to achieve, it is usually necessary to combine multiple types of data analytics in order to achieve a high confidence conclusion that can successfully be used to inform strategic decision making. The garbage-in-garbage-out concept applies strongly, as planned outcomes are only achievable if the data is of sufficient quality and accuracy.
