Ashley Holmes
ACC 235 – 11:00 am
Debbie Lindberg
March 9th, 2016
Introduction
“Never before in history has innovation offered promise of so much to so many in
so short a time.”Bill Gates stated this quote to educate the world about innovation. Innovation
comes to the world without warning and makes a lasting impact. The reason people struggle with
innovation is because innovation does not give the users the choice to adapt to the innovation or
not. Innovation simply becomes to new norm and the users and society around it must adapt to
the innovation.
This concept of innovation also applies to the business world and the
accounting/auditing industry. The profession is making much better use of the technological
advances that we’ve seen over the last 20–30 years,” said James Comito, CPA, the national
director of the Professional Standards Group at Mayer Hoffman McCann PC (Maria L. Murphy
and Tysiac). Big Data and data analytics will be the next innovator to come upon the auditing
industry. With this new wave of innovation, there will be opportunities, challenges, and ethical
implications.
Definition
Knowing and understanding big data is the first step in preparing and adapting to this
new innovation in the auditing industry. Big data is a term that describes the large volume of data
– both structured and unstructured – that inundates a business on a day-to–day basis. But it’s not
the amount of data that’s important. It’s what organizations do with the data that matters. Big
data can be analyzed for insights that lead to better decisions and strategic business moves
(Dean)
Big data is essentially data gathering at the roots and the act of gathering and storing
large amounts of information for eventual analysis is ages old. Although data gathering is not an
innovative concept, big data is a new area of innovation for the auditing industry for this century.
The concept gained momentum in the early 2000s when industry analyst Doug Laney articulated
the now-mainstream definition of big data as the three Vs: volume, velocity, and variety. Laney’s
three Vs help define to complexity of big data and define a deeper understanding.
Big data is so complex for the auditing profession because businesses have a high volume
of data. Organizations collect data from a variety of sources, including business transactions,
social media and information from sensor or machine-to-machine data. In the past, storing it
would’ve been a problem – but new technologies (such as Hadoop) have eased the burden
(Dean).
