MANAGEMENT ACCOUNTING
DECISION MAKING AND
CONTROL
BIG DATA ESSAY
MARCH 9, 2020
HAUWA AUWAL AHMED BAFFA
1615824
Word count: 1943
Introduction:
As the name implies, big data is data that surpass the processing capacity of the
traditional data base (Vasarhelyi, Kogan, and Tuttle, 2015). Data that is
considered to be big in one company, may not be in the case of another. This
depends on the size of the company, and the nature of their operation. For
example, the data that will be determine as big in the medium sized accounting
firm, could not be big in the Big 4. It is a fast growing concept which seems to be
applied in almost every activity. The main Aim of big data is to provide output
which will help gain business solutions and allow dramatic cost reduction, by
improvement in time required to perform computing task.
continuous development of machine learning and automation, in addition to ability
to interpret and analyse big data, has increased the uncertainty across variety of
jobs. With likelihood of individuals being faced to be replaced in the future through
automation (Frey, and Osborne 2013). The issue has been a subject of debate
over a long time . For example in “Economic Possibilities for our Grandchildren”
(Keynes 2010). Which Keynes characterised the future, as period of quick and
rapid change in economic and working condition, hence giving rise to problems
relating to adjustment and labour absorption. So also, in the “Autonomous
Technology: Technics-out-of-Control as a Theme in Political Thought” (Winner,
1978).
The essay will start by defining data, and further discuss some of the challenges
and opportunities of using big data with regards to auditing, management
accounting and financial accounting.
Types of data:
Data is mainly divided into; structured and unstructured form of data. Structured
data is that data that is generated typically from firms processes and transaction
systems. For example inventory management system, customer management
system. This data well organised, and easily processed through the traditional
database. Unstructured data on the other hand, originate from a wide variety of
sources. For instance, social media, and can be in the form of text, video, or
images, or audio. Hence, unstructured data represent by far data that lacks rigor
structure of a firm and results to need for more complex system to help in
processing and interpreting the data (Beath, Becerra-Fernandez, Ross, and Short,
2012; Gandomi and Haider 2015).
Bigdata is characterised by its volume, velocity and its variety. Volume wise, the
size of the data available now is in grand scale, which makes it more difficult to
be evaluated using the tradition tools. So also, considering the pace at which both
the economy and the technology is changing, high velocity is needed for efficient
processing. Therefore, big data are produced and processed continually, rather
than on a one-off basis (Kitchin, and McArdle, 2016). In addition, earlier
researchers (O’Connor, 1912) seems to be focusing more on the wide variety of
data, which according to recent research, it is argued that the concept of variety
has been in organisations for a long time, although been hoarded due to
unavailable of technology to process the data (Gandomi and Haider 2015).
Audit:
Public accounting firms are said to face unique challenges in the revolution of Big
data. This may be in the form of rise in level of competition from technology-based
companies which have competitive advantage in data analysis (Richins, Stapleton,
Stratopoulos, and Wong, 2017), such as FinTech and Google. Although, David
(2015), suggest that audit is one of those professions that consist of division of
tasks, which collectively are not easily automatable. Over the years, auditors apply
their data analytic mainly on data generated through their client’s accounting
system, which have immanent structure, and have limited size of data. Having
said that, in the future, auditors must capitalise on the opportunity on learning to
apply their data analysis approach on a much larger dataset, and also analyse
unstructured form of data set in other to stay competitive (Brown-Liburd, and
Vasarhelyi, 2015). And currently this trend has been starting to be followed by the
Big 4. For example, KPMG LLP has gone into partnership with IBM to use IBM’s
