How VirtualZ’s Built-In Data Exclusion Delivers Precision, Performance, and Governance from Mainframe to Cloud
When enterprises move data from legacy systems like IBM Z to modern platforms for AI, analytics, or compliance, they often run into a critical — but under-discussed — requirement: data exclusion.
At VirtualZ, we’ve built data exclusion into the core of our no-code ELT platform, PropelZ™, because we believe you should only move the data you want — and nothing more. That means faster performance, tighter compliance, and fewer headaches for your teams. In this post, we’ll break down what data exclusion means, how it works in PropelZ, and why it’s a big deal for enterprise customers and systems integrators alike.
What Is Data Exclusion?
Data exclusion is the ability to intentionally omit specific fields or records during data extraction. It’s not just about filtering; it’s about granular control over both:
- Rows (records) — Which records should be included or excluded from the extract?
- Columns (fields) — Which fields in each record should be included, suppressed, or redacted?
Imagine you need to move customer files to the cloud but want to exclude Social Security numbers or filter by department (e.g., only R&D employees). With PropelZ, you can do both—easily and securely.
PropelZ: Built-In Control with Zero Code
PropelZ gives you multiple layers of data exclusion and filtering — all without writing a single line of code. Here’s how it works:
Row-Level Filtering
- Key-Based Filtering: Filter using VSAM keys or record numbers. For example, only extract records between two department keys.
- Expression-Based Filtering: Use regular expressions to define exactly which records should be processed. Want only records from Mexico? With a few lines of config, PropelZ can do that.
- Record-Type Filtering: In files with mixed record types (e.g., transactions vs. addresses), extract only the records you need.
Column-Level Filtering
- PropelZ uses metadata to define which fields to include or suppress. Sensitive fields like SSNs can be marked as FILLER, ensuring they’re never processed, transferred, or stored on the target.
Performance Gains, Too
This isn’t just about compliance — it’s also about speed and efficiency.
By filtering data before it leaves the mainframe, you dramatically reduce:
- Data volumes sent over the network
- Processing time in the cloud
- Storage costs and query complexity on the target
Example: A demo file with 80,000 airport records (1K each) could be trimmed to 100 lightweight records with only 1–2 needed fields — cutting total data volume by over 90%.
Every Run, Your Rules
PropelZ lets you define different exclusion rules for every run. That means:
- One user can get a redacted version of a file.
- Another can see the full version.
- Both can pull from the same input file — just with different metadata configurations.
This dynamic, run-by-run flexibility makes it perfect for multi-tenant environments, internal user segmentation, or client-specific pipelines.
One Product, Not Five
With many vendors, delivering data exclusion often means piecing together:
- One product for masking
- Another for movement
- A third for transformation
With VirtualZ, you don’t need multiple products or layers of complexity. Everything — exclusion, transformation, movement, and security — is built into PropelZ. It’s all:
- Integrated
- No-code
- Config-driven
- Flat-priced at $235K/year per customer
That’s what makes VirtualZ different.
Why It Matters
We don’t just support data exclusion. We made it a first-class feature — because real enterprises need more than just “lift and shift.” They need precision. Governance. Performance. Control.
Next Steps
- Schedule a PropelZ briefing.
- Watch a demo of PropelZ.
- Try PropelZ.
Learn More
- Visit our Customer Briefing Center.
- Review all VirtualZ Use Cases, Thought Leadership papers, and Solution Briefs.
- Explore our YouTube channel, podcasts, and blog.
- Still have questions? Contact us.