Handels-Software-Partner GmbH has launched the new GDPdU Viewer (Opti.View) and renewed its certification for the rapid data analysis software InfoZoom.

hsp GmbH has recently been recertified by humanIT Software GmbH for its rapid data analysis software, InfoZoom. The long-standing partnership between humanIT and hsp is, as it were, being given a new boost by the launch of the new product, GDPdU Viewer.

GDPdU data: a black box

With its data analysis tool, GDPdU Viewer, hsp GmbH provides a useful tool for all businesses that wish to be on the safe side in the event of a tax audit:
Whilst most ERP systems are capable of outputting the required GDPdU data in a legally compliant format, this does not mean that the quality of the data is clear and visible – in other words, where and whether inconsistencies are apparent, which usually lead to unpleasant enquiries. In such cases, the data provided remains a black box.

See what the tax inspector sees

This doesn’t have to stay that way, as the GDPdU Viewer sheds light on the matter. The software makes it very easy to import GDPdU-relevant data and visualise it for the business owner. This allows business owners to examine the very same data set that the tax inspector will be scrutinising. The advantage is that you can correct any erroneous data sets before the audit takes place. As the volume of data is usually enormous, the GDPdU Viewer also offers the option of analysing the data in detail.

CTA Box Opti View

Analyse data at the click of a button

To this end, the GDPdU Viewer utilises InfoZoom, a fast and straightforward data analysis software that enables any type of analysis at the click of a button, using multi-layered templates, without the need for specialist IT knowledge. Based on its InfoZoom certification, hsp also offers bespoke services covering, amongst other things, the following areas of analysis (extract):

  • Analyses based on Benford’s Law
  • Chi-squared analysis
  • Checking the plausibility of invoices

As tax audits involve the use of identical or similar analytical methods, companies thus have the opportunity to clean up their data sets before the „worst-case scenario“ has to materialise.

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