source: cio.com

(Found the paper I wrote for AAS’s pre-departure training assignment when tidying up my computer files and decided to post it here since why not. Hehe. Pritania Astari and Nadhya Fitri peer-reviewed and Barbara Wiechecki a.k.a the best tutor (*wink) final-reviewed it.)

In today’s world, there is a popular refrain “The world’s most valuable resource is no longer oil, but data.” (The Economist, 2017). Back in 2013, Deloitte published a report titled “data is the new gold” to support the idea about the importance of data for organisations. It is not surprising that now many organisations regard data as a strategic asset. With the growing awareness of the significance of data for organizations, arises the demand for auditors to sustain their relevance by utilising data analytics techniques. Data analytics involves the analysis of the entire sets of data to identify anomalies and trends to provide audit evidence as well as insight for further investigation. This process usually incorporates an analysis of overall populations of data, rather than the widely-used approach of only inspecting a small sample of the data (Bragg, 2019). With that qualification, no wonder data analytics is considered one of the most important technological advancements that should be implemented in the auditing process.