How do we Trust Data?

Data could be categorised as reliable and trustworthy on the basis of its stability, reliability and measurability. A trustworthy data becomes very valuable for companies so as to enable them to understand the variables that define their businesses. Often it takes data of multiple years to get the maximum value. More data means more confusion about reliability of the data. Selective kind of data that could be called reliable would be:

Experimental Data: Meticulously designed and controlled experiments which are conducted by rational third parties with expertise in such experiments give out the most trustworthy data. The noise from the signal is distinguished with the aid of effective controls and sophisticated statistical analysis.

Survey Research Data: Scientific Research studies that are conducted by experienced professionals give out trustworthy data. This data is often again experimental in nature. Noise is often minimal and research design, normative data, modelling techniques, control of stimulus and the quality assurance standards ensure precision in the data.

Sales Data: The third ranking in trustworthiness of data could be of the sales data. It is pretty good but certainly not perfect measures of the actual sales. Sales are in themselves not very reliable and valid measures of the factors that determine it. Sales data fail when it comes to studying cause and effect. To understand it better the strength of sales data lies in determining what happened but may fail in measuring why it happened and what were the forces that caused it to happen.

The other types of data that may follow suit in ranking when it comes to establishing trustworthiness of data would be the eye tracking data, The biometric or physiological measurement of data, data gathered from communities or advisory panel and not to forget the latest buzz word the social media data which is considered to be the easiest and fasted source of data collection but it has its own drawbacks and challenges.

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