Opportunities and Challenges of Big Data in Accountancy

Opportunities and challenges of big data in accountancy
Introduction
Big data is a term widely used in the business environment in the current years. The term is too
broad that the professionals are keeping their minds and professionalism together to come up
with a simplified comprehensible definition. Growth of competition in business environment and
advanced development of technology have in the current world have made businesses to fight
their way out for survival in the market through acquisition of big data (Boons, Frank, and
Florian Lüdeke-Freund. 2013). Businesses are nowadays changing from small data to big data to
enjoy the benefits it encompasses. So much advantages are enjoyed from incorporation and
adoption of big data by big data users Gandomi, Amir, and Murtaza Haider, 2015). Big data is
therefore be defined as extremely vast volumes of complicated data that are beyond handling
using the traditional tools but rather require sophisticated analytical methods to handle.
Structured, semi-structured and unstructured are the three major types of big data. Data bases
that would be used to handle big data will depend on the structure and type of the collected data
(Wamba et al. 2015). The collected data fit the whole business needs as they are directly from
their consumers ranging from their views concerning the supplied products by the business to
their test for the products and the business services among other views. Each business
department thus get their portion from the leveraged big data including the marketing
department, purchase department, sales department, accounting department etc. each department
tighten their waste towards meeting the objectives of the business as the requirement of the
current market obtained from the leverage of big data. Even though bid data have become so
lucrative to businesses and have now been adopted for use by variety of business companies, the
idea and the relevance importance is still very new and fresh in the business accountancy. In this

essay, we shall discuss some of the opportunities that can be enjoyed and challenges associated
to them when using big data in accounts.
Opportunities of big data in accountancy
Accounting professionals and the business community at large should embrace the opportunities
that are accompanied by the adoption of big data and data analytics to help them improve on
their efficiency, effectiveness and efficacy in their work (Abbasi, Ahmed, Suprateek, and Roger.
2016). The initially used spreadsheet is now replaced by big data as millions of data are collected
in business databases that are too large to be handled by spreadsheets (Boons, Frank, and Florian.
2013). The highest percentage (98%) of stored data currently in businesses are electronic where
the percentage was weighed much lower (25%) in the past decade. The percentage have had such
rapid increase due to velocity at which big data is collected and stream in the databases. Both
structure and unstructured data are collected in the businesses including the scanned documents,
emails, voicemails, images and social media as is experience with Walmart’s (Loebbecke,
Claudia, and Arnold, 2015). Customer engagement in business can be automatically changed in
business by providing forecasting analytics for business decision making and also automating the
operation process.
Incorporation and adoption of big data in accounting exist in two different ways i.e. through
integration of different data sources into the accounting information systems and through
collection and evaluation of designated data that come from different sources particularly those
concerning the fair value assets and liabilities resulting to assumptions on fair value estimates.
Connections created between videos, texts and audios to the traditional data in the accounts
department need to be looked into exhaustively to the bottom bit of them. In that response
therefore, the accountants are supposed to hone their data analytic skills so that they can easily

deal with vast volumes of data available at their desks that is not to exclude automatically mined
data. In the areas where big data have effect on considerable change is fair value accounting
where scattered financial data are collected and merged into unit data that can be used in
valuation workflows (Najafabadi et al, 2015). That formed the big opportunity that could be
grasped by the financial accountants from the big data leveraging.
Big data also provides opportunity to the managerial accountancy by posing challenges and
opening their eyes and minds in their accounting management roles (Garonne et al. 2014). The
dynamic change in business environment requires dynamic responses from the accounting
professionals as brought forth by big data adoption. Due to that therefore, accounting personnel
should change from being decision making supporters to the business partners but to give value
input to business and extract evidences from big data that could be used in business rather than
relying on the views of the management officials. Accountants in the accountancy positions
should have the awareness of the cybercrime and that should sound a warning to them not to
store too sensitive financial data in the cloud to avoid cyber-attack (Lee, Jay, Behrad, and Hung-
An. 2015). Big data can as well improve the performance of the company since the financial and
accounting department could compute and compare the means of the collected data to the
currently existing financial data mean and tell whether or not there was improvement in the
business performance (Warren et al. 2015). Adopting big data and their data analytics techniques
can make it easier for the business to control employees’ work telephone calls and emails if
comprehensive monitoring and control systems are adopted. Vast volumes of non-financial data
such as social media and website are created by businesses of small scale and large scales. In the
current world, financial statements and transactions represent businesses traditionally (Soetanto,
Danny and Sarah, 2013). Descriptive analytics on big data help to bring numerical meaning from