Limitations of traditional data analysis

 Limitations of traditional data analysis  

When analyzing data, it can have some limitations that will affect the overall usefulness or of the data. The data’s quality is based on its limitations.

Data quality — The data’s quality is measured based on if there are any biases, mistakes or missing data.

Sample size — The data size is measured based on the actually size of the amount of data collected from the people questioned. The more people that are questioned the more valuable the data is due to it being more accurate. This is often hard though costing a lot of time or money.

Limited scope — f they have a limit scope of what the data should be the data will be limited in scope. This will make the data useless. 

Assumptions — In most data analysis methods people make assumptions about there data. A common assumption made during these data analysis is that the questions were handed out equally to people and there was no bias in who they choose or how different the people they are asking are. If not done correctly could build a bias analysis that is useless.