<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Case Studies: AI Automation for DACH on René Zander | AI Automation Consultant</title><link>https://renezander.com/case-studies/</link><description>Recent content in Case Studies: AI Automation for DACH on René Zander | AI Automation Consultant</description><generator>Hugo</generator><language>en</language><lastBuildDate>Tue, 21 Apr 2026 12:00:00 +0000</lastBuildDate><atom:link href="https://renezander.com/case-studies/index.xml" rel="self" type="application/rss+xml"/><item><title>German PII Redactor: Covering the 5% Blind Spot in SAP Data Masking</title><link>https://renezander.com/case-studies/de-pii-redactor/</link><pubDate>Tue, 21 Apr 2026 12:00:00 +0000</pubDate><guid>https://renezander.com/case-studies/de-pii-redactor/</guid><description>&lt;h2 id="the-problem"&gt;The problem&lt;/h2&gt;
&lt;p&gt;Every SAP shop copies production data into dev, QA, and training landscapes. It is how you reproduce customer bugs on real payloads, load-test a release, and train end-users on data that looks like what they will see on Monday.&lt;/p&gt;
&lt;p&gt;Every copy is a compliance event. &lt;strong&gt;DSGVO, Art. 5&lt;/strong&gt; requires personal data to be processed only for legitimate purposes and pseudonymised where practical. Most DACH enterprises have bought a deterministic masking tool — SAP TDMS, Delphix, Informatica TDM, IBM InfoSphere Optim — and wired it into the copy job. The tool rewrites classified columns: &lt;code&gt;KNA1-NAME1&lt;/code&gt; becomes &lt;code&gt;Mustermann&lt;/code&gt;, &lt;code&gt;BSEG-IBAN&lt;/code&gt; becomes a fake IBAN that still passes checksum, &lt;code&gt;USR02-BNAME&lt;/code&gt; becomes &lt;code&gt;USER042&lt;/code&gt;. That covers the ~95% of PII that lives in schema-aware, row-level columns.&lt;/p&gt;</description></item></channel></rss>