The audit industry is being pushed for more data analytics, so does this mean that auditors need to be able to work with big data? The two terms are often used interchangeably, but they really mean two different things.
I was at a conference a couple of years ago where college and university educators were meeting with accounting firms to discuss how they could work together to best prepare students to graduate and hit the ground running as auditors. At this conference, the terms big data and data analytics were sometimes being tossed around interchangeably. Finally, one of the representatives from a Big Four firm addressed the educators and said, “We don’t need you to produce graduates that can deal in big data, we have people for that. We need you to teach the critical thinking skills that auditors need and that apply to data analysis.”
Also adding confusion to this topic, the definition of how big data needs to be to be labeled “Big Data” varies. Sometimes this is defined by the tools required to work with the data. For some, that means if it’s too big to fit in Excel, a little more than 1 million rows, it’s Big Data. For others, the data must be much larger and other data analysis tools and platform limits define “Big Data.”
It’s my experience that data analytics in the audit world, or what we sometimes refer to as audit analytics, has been a challenge for some auditors. Some of it I think is due to auditors not giving themselves credit for data analysis that they may already be performing. Sorting, filtering and summing worksheets, and inspecting those results should be considered data analysis.
In other cases, the challenge is because other audit analytics tools were very difficult to use requiring programming and DBA skills. However, we designed TeamMate Analytics to work within Excel, so it’s easy to use and helps auditors bridge beyond basic Excel functions into more advanced audit analytics work.
For most audit analytics, Excel worksheets can hold all the data, but there may be some occasions where larger datasets need to be analyzed. Therefore, we enhanced TeamMate Analytics so that record sets of tens of millions of records, or more, can be processed through a Custom Module. Custom Modules are not new. Auditors have had the ability to create Custom Modules containing one or more tests to perform on a set of data. What’s new is that a Custom Module can read in an external source such as a .csv file containing millions of records and virtually the same tests can be run on the data regardless of the data source is an Excel worksheet or a much larger source such as a .csv file. So, auditors can work with much larger data sets still within TeamMate Analytics’ easy to use environment.
With TeamMate Analytics now enabling auditors to easily perform data analytics on large data sets, perhaps the line where data becomes “Big Data” will change for many auditors.