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The next frontier in data analytics Logo aicpa

  Norbert Tschakert, CPA/CFF/CITP, Ph.D.; Julia K... |   Free |   AICPA |   01 Aug 2016 |   Journal of Accountancy

This article discusses why CPAs and organizations need to learn to use advanced technology to predict and achieve outcomes.

Topics covered:
  • Assurance: Technical: Audit: Data analytics, Intermediate
  • IT management & assurance: Technical: Information management: Data management & analytics, Intermediate
  • Firm practice management: Technical: Practice growth , Intermediate
  • Forensic & valuation services: Technical: Data analytics, Intermediate
  • Personal financial planning: Technical: Practice management & professional standards, Intermediate
  • Management accounting: Digital skills: Data analytics, Intermediate

4 Comments/Reflections

Kamini Doorsamy

Kamini Doorsamy Jun 2019

Data analytics ensures that companies can gain a competitive edge and investment in this field is important if companies want to remain relevant and profitable.
Christopher Jonas

Christopher Jonas Aug 2018

The article gave a great insight into the development of data analytics, with the emphasis on predictive analytical tools and taking into account many data sources business can utilise data to develop strategy. The role of the traditional accountant will inevitably evolve into data "engineer" type roles but it is important to understand the source of the data and how it can effect the business. Highly dependent upon skills training and staff development.
Bipin Hathi

Bipin Hathi Jun 2018

Data analytics is being widely used in the tax area too. I have see first hand how programs are being used to identify opportunities where tax has not been claimed or areas where compliance needs to be improved. The tax authorities are also using tools to carry out audits which is saving them time and pin pointing areas where there is tax leakage.
Dengmei Xia

Dengmei Xia Dec 2017

Analytics skills are more and more important. Data analytics includes not only descriptive analysis but also predictive and prescriptive analysis. However, it is hard to do predictive and prescriptive analysis well. I also need improve my skills.
As author says, good technical skills, understanding of the business context and analytical mindset are necessary factors to be an ideal "analytically skilled" employee. I think I have already understood the data and knew how to manipulate it. I also possess an inquiring nature and intellectual curiosity. The most lacking is understanding of the business context. In other words, I do not know enough about the business. It will be my direction to improve my understanding of the business context.