St John, Parker
ACC 235 | LINDBERG
“Big Data”
THE EFFECTS IN BUSINESS AND AUDIT
Intuition, Instinct, natural skill, is being replaced in many fields by the efficient and
effective analysis of “Big Data.” Big data has become more and more useful as technology has
created the means to store, analyze and implement consequent solutions. As does all tools of
efficiency, they come at a cost. Privacy, security, misleading data, replacing jobs and making
prior efforts obsolete. These inherent and potential risks are considered necessary to improve
internal controls and automate detection of certain material misstatements. The future of audit
and accounting is likely to be dominated by automated processes resulting from the collection,
analytics, and decision making based on the usage of big data. Morale implications from big
data call upon the larger morale dilemma of how individuals and humanity collectively feels
about artificial intelligence. The opportunities are kind of obvious, minimizing risk and error,
highlighting anomalies, efficiently processing data while minimizing data redundancies. The
opportunities can be endless pending on how the data is utilized. When considering how or if a
firm wants to utilize big data they must consider the opportunity cost of how their current
processes will be changed and the actual cost of software sufficient to meet their needs.
Overall, big data is a powerful cluster of information that can change industry as we know it, it’s
effectiveness is indisputable, but how it changes the day-to-day processes of the individual
employee is yet to be seen.
Big data’s definition seems to be both ambiguous and subjective to each firm based on
their needs and subsequent usage however, according to the article, Undefined By Data: A
Survey of Big Data Definitions, “Big data is a term describing the storage and analysis of large
and or complex data sets using a series of techniques including, but not limited to: NoSQL,
MapReduce and machine learning.” (Ward and Barker 2013) Most definitions, “…make at least
one of the following assertions: Size: the volume of the datasets is a critical factor. Complexity:
the structure, behaviour and permutations of the datasets is a critical factor. Technologies: the
tools and techniques which are used to process a sizable or complex dataset is a critical
factor.”( Ward and Barker 2013) Commonly associated with the definition of big data is the
three V’s: volume, velocity and variety. In reference to big data Volume is defined as the scale
of data (size), variety refers to the different forms of data and velocity refers to the analysis of
streaming data (speed) according to IBM (“The Four V’s of Big Data,” n.d.). In some firms, some
definitions of big data incorporate a fourth V, the one most commonly represented in my
research was veracity, which refers to the uncertainty of data. (“The Four V’s of Big Data,” n.d.)
