Data analysis is the breakdown of information (data) into segments that help to make
informed decisions. For the information to be useful, there must be a well thought out
approach answering several questions; what data is required, how will the data be analyzed,
and how will the results help support the response. It is important to take into regard the
limitations of the data as well, such as missing data, altered data, data form, data definition,
unretained data (Robert Rufus, 2015). b Other considerations are time constraints, access to
the data, and technological resources.
To obtain the data it must come from a reliable source.
• The first party data comes directly from the individual or entity and is the most
meaningful.
• The second party is a source that is connected to the subject and may have firsthand
information.
• Third party data is data that has been retained from an outside source such as a
governmental agency or financial institution.
• Fourth party data is not specific data but more informative of the subject’s
environment (Robert Rufus, 2015).
A good analysis is dependent on the data being sufficient and relevant. AICPA Rule 201
requires there be sufficient data to allow for reasonable conclusions or recommendations.
Sufficient should be in quantity and quality and is supportive of the opinion. Relevant is
dependent on the actual purpose for the engagement which guides what type of data should
be obtained (Robert Rufus, 2015).
References
Robert Rufus, L. M. (2015). Transforming Data into Evidence (Part 1). In L. M. Robert Rufus,
Forensic Accounting 1st Edition (pp. 227-246). Pearson Education.
