What Problems Of Secondary Data Quality Must Researchers Face? How Can They Deal With Them?

Although using secondary data can sometimes be a quicker and more cost-effective way of conducting research, there are a few negatives that come with not doing the initial research or data-compiling yourself.

The main problems of secondary data quality researchers must face are:

• Reliability

This is really the main issue when it comes to the validity of secondary data. If you conduct your own research experiment or took your own notes at a meeting or speech then you are completely sure that what is down on paper is a correct representation on what happened. However, being given secondary data is basically taking someone else's word for something. The information and data can be of great importance and so can be used, however, the validity of the source will always come into question.

• Dealing with the validity issue

For researchers to successfully get around the validity issues of using secondary data they usually need to carry out more background checks themselves. Of course, this eats into research time and can sometimes turn what looked like quick secondary data into primary data due to the extra research. It can be comparing a transcript of a meeting or experiment with someone else's transcript of the same date.

It may seem somewhat of an arduous task, however, it is necessary to prove validity and make it useful to use, otherwise it could bring the whole research and conclusions into serious question.

Therefore secondary data, although seen as quicker and easier to access, comes with many issues and if they are not successfully addressed then the data becomes rather unreliable and therefore worthless to the bigger picture.