When designing an experiment it is important to first identify the level of information required, then select the appropriate technology. Low coverage techniques will be low cost and allow measurement of many samples. High resolution full coverage approaches, while providing more information are often too costly to measure many samples. A sufficient number of replicates is required to made meaningful conclusions, choosing the right technology for an experiment is therefore vital. Depending on the data produced the types of data analysis will differ considerable. Simple techniques like PCR will produce simple results with simple analysis outcomes. More complex analysis techniques will produces more complex results, which will require substantial data storage space and computational power to analyse. It is best to familiarise yourself with the data analysis steps and requirements before generating data.