Are your data skills transferable?

content data skills

The knowledge of data analysis needed in corporate roles is different from – but not incompatible with – that used in audit.

Auditing is often a first job for trainee accountants. It provides a solid foundation for all future business roles. But audit working can be challenging – in top firms, the competition is fierce and long hours are common. In addition, many predict that technological advancements will lead to massive contraction in the audit profession.

Obtaining data analytics skills could be the best way forward for those looking for opportunities outside of audit. For professional accountants or trainees who choose to move on to pastures new, it’s useful to understand the key skills differences needed in corporate versus audit roles.

Reporting frequency

In audit, you interact with the client’s database once a year, so your focus on data extraction is minimal. Working in the finance function of a business, you deal with the same database continuously, monitoring the closing of accounts and updating management reports each month.

In a business, you repeat the same tasks at least 12 times a year. In fact, a lot of tasks are done repetitively in the same environment, so automation is usually necessary. For auditors, on the other hand, it’s sometimes best to extract the data manually and spend most of your time on audit procedures.

In addition, analysis and management reporting within a business takes place at least monthly. This frequency means data-modelling skills are needed in order to link the data clusters into models. Otherwise, analysis is highly susceptible to errors and not available for ad hoc requests or responsive to changes in management’s needs.

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Direction of data analysis

In audit, the focus tends to be on historical information, from the past year, with only a minor look forward when addressing issues around going concern. But the audit relies heavily on analytics.

In business, past information is also relied upon, such as for budgets and monthly management reports. Data analytics are also important, as management reports contain versatile visualisation, which is also often interactive. So the auditor’s experience will equip them well for performing data analysis within a corporate role.

However, more senior accountants also need to model for future scenarios and strategies, so skills will be required here.

In my next article I will look at the various data analytics software programmes on the market and compare their functionality so you can get an idea of what is being used and why.

Types of data analysis

There are three types of data analysis: descriptive, predictive or prescriptive. Auditors looking to switch into roles within businesses might bear the following in mind:

  1. Auditors already have some knowledge of descriptive analysis due to their experience in financial analysis. It would not be a huge leap to learn data extraction and visualisation skills.
  2. The highly repetitive nature of the work requires knowledge of data modelling. The auditor would need to learn about relational databases to obtain those skills.
  3. Knowledge of data science is helpful if you’re looking to get promoted to senior roles (see ‘financial data science’ sector in the graphic).

Author: Yeldar Rakishev ACCA

More information

This article was first published in Student Accountant in April 2023Get the SA app now

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