Once you’ve chosen a data set that you believe will work, take care to carefully evaluate it. Why is it important to evaluate our data and ensure that we are using quality data? Data that has been organized and interpreted into sets, phrases, or patterns, becomes information. We use information to identify needs, measure impacts and inform our decision making. If the data underlying that information are incorrect in some respect, then our decisions and result could also be wrong or misleading.
Ask yourself, does the data cover your Who, What, When, and How requirements? Always read the metadata and documentation to ensure that the analysis you are planning to do really measures what you want it to.
The “who” factor impacts the data’s reliability and whether or not we ultimately opt to utilize or trust it. Data from sources like professional organizations or government agencies will have a reputation for trustworthiness not commonly associated with data gathered from less credible sources. Consider the extent to which the data producer is perceived as authoritative on the subject matter.
It's important to gauge objectivity and intent, especially when examining data from commercial businesses or say political parties. Is there an incentive to be biased? The integrity of such research might be compromised, so think critically of the data you find.
Depending on the nature of your research question, it could be important to find the most accurate and relevant information available. This holds true especially when seeking data about the latest trends in a particular industry, for instance.
What methods were used to collected the data? What methodology was used? Consider comparing to other similar research to see if any inconsistencies arise.