Generic Self-Service Data Prep Tools Can’t “Taxify”

  • February 26, 2018

As organizations increasingly use self-service data preparation tools, tax professionals should distinguish between generic versions of these applications and domain-specific self-service data prep tools that address the unique demands of tax management requirements. Generic data prep tools have limitations – most notably, difficulty “taxifying” data – that tax folks should recognize before asking their IT colleagues to invest in these types of applications.

Self-service preparation tools were developed to address the growing use of data analytics by business users needing less support from their IT teams. The functionality of these tools, which can cost as little as a few thousand dollars, enables non-IT users to gather certain types of raw data to feed a range of analytics.

However, when it comes to analyzing tax data, generic self-service tools tend to be too broadly designed. As a result, these applications typically require extensive customization to conduct effective analyses of tax data. These modifications, when performed by third-party experts, can send the total cost of ownership soaring past six figures. However, they are necessary due to large amounts of data that tax needs to be “taxified” – that is, converted from general business data to data with a tax-specific view (i.e., legal entity data). This conversion requires extensive data manipulation guided by tax-specific logic. The sheer amount of data that tax manages also poses a challenge to many generic self-service data prep tools, which cannot handle high volumes of data.

To be sure, generic self-service data preparation programs have a number of beneficial applications across most – but not all – corporate functions. Tax professionals interested in self-service data prep tools should look for tax-specific applications or functionality within tax management software. Choosing a tool that comes with a defined tax data model and the ability to source, clean, validate and unify the raw data that feeds the model can help tax professionals avoid submitting ill-advised purchase requests to their IT partners.

If you have any questions, or experiences, regarding self-service data preparation tools, please leave a comment for me here.

Please remember that the Tax Matters provides information for educational purposes, not specific tax or legal advice. Always consult a qualified tax or legal advisor before taking any action based on this information.

About this Contributor

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Jen Kurtz
Chief Technology Officer

Jen Kurtz is the Chief Technology Officer focused on technology strategy and product innovation. Jen leads the Office of Technology responsible for bringing together the technology vision, strategy, architecture, and capabilities required to drive breakthrough innovations that will propel Vertex forward in seizing new market opportunities.

Previously, Jen served as a lead member of the software development and commercial enterprise architecture teams. Prior to joining Vertex, she was a software engineer at Verizon and Platinum Technology respectively bringing large scale business applications to the market.

Jen has been honored by Oracle for Women’s History Month and Working Mother Magazine at their annual Working Mother 100 Best Companies event. She regularly speaks at local and national technology conferences and has an M.S. in Computer Science from Villanova University and a B.S. in Computer Science from Bloomsburg University of Pennsylvania.

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