Data Classification Guide
A technical guide explaining why data classification is critical, how it works, and how it can be implemented in enterprise environments.
Data Security / DLP / Security Engineering
Aziz Ortanç
Senior Cyber Security Engineer
I design and operate enterprise data protection controls across DLP, data classification, ICAP integrations, endpoint security, and the infrastructure that keeps them reliable.
What I Specialize In
A compact view of the work: from data protection controls to the infrastructure and enablement practices that make them usable.
Data Protection / Product Intelligence
DLP, data classification, and discovery work backed by requirement analysis, vendor capability mapping, PoC scope design, and practical validation points.
Infrastructure / Traffic Analysis
Comfortable across Windows/Linux services, directory and network foundations, security data platforms, firewall flows, and packet-level troubleshooting.
Implementation, Automation, Prototyping
Bridges hands-on implementation with scripting, documentation, customer enablement, and fast side-project prototyping.
Engineering Habits
[01]
Start With the Problem
Good technical work starts with analysis, research, evidence, and a clear definition of what needs to be solved.
[02]
Understand the Flow
Inspection is safer when the protocol, queue, timeout, and failure path are understood before rules are added.
[03]
Design for Bad Days
Security systems need predictable behavior during load, outages, updates, and partial failures.
Operating Notes
- Start with evidence before touching configuration.
- Design controls with latency, recovery, and ownership in mind.
- Keep automation readable enough for the next incident.
- Turn complex systems into clear handover notes.
Technical Skills
A practical map of the engineering areas I use while designing, deploying, and troubleshooting security controls.
Security / Product
DLP architectures, data classification, data discovery, endpoint security, mail/web channels, and ICAP-based enforcement flows.
Infrastructure / Data
Windows and Linux servers, domain services, MongoDB and Elasticsearch clusters, log management, hardening, recovery, and operational troubleshooting.
Analysis / Automation
Packet analysis, protocol inspection, log correlation, Bash/PowerShell automation, REST API usage, technical documentation, and repeatable operational workflows.
Technical Writing
Short technical writing on data protection products, infrastructure troubleshooting, protocol analysis, and security engineering practices.