Dear Diary,
Today I left the house again. I thought my life would be simple, maybe settle into a spreadsheet and hang out for a while. Instead, I’m a frequent flyer in every modern organization. I have more passport stamps than a travel influencer, and my luggage always gets lost.
If you’ve ever wondered what happens to your personal data after you submit it to an organization, buckle up. It’s a wild journey.
Meet the Traveler
Hi, I’m a piece of personal data: information that relates to an individual, whether it identifies a person directly or indirectly.
I travel with a passport full of identifiers: email address, customer ID, phone number. My luggage includes baggage tags in the form of metadata: timestamps, IP addresses, device details, and sometimes location approximations.
As a piece of personal data, I fly economy and go through standard security. However, some of my friends are more sensitive under certain privacy laws: think health information, biometrics, precise geolocation, government identifiers, or children’s data. In fact, some of my more sensitive data friends receive the VIP treatment. Because organizations must implement robust security measures to protect sensitive data, this data flies first class, ensuring it receives the best care. That usually means tighter rules, stricter access controls, and more supervision over where we’re allowed to go.
✈️ Travel Tip: If you wouldn’t recognize everything in the suitcase, it’s time for a data inventory.
Check‑In
My journey today began with a newsletter sign‑up form. In exchange for 10% off your next purchase, I’m now booked on a trip with fast‑moving itinerary. Data like me checks in through all kinds of desks: website forms, mobile apps, customer support tools, in‑store systems, field applications, and B2B lead capture forms.
At check‑in, I get two things:
- A ticket, representing the organization’s permission to send me on the trip. Sometimes that’s consent. Other times it’s because the trip is necessary to perform a contract, comply with a legal obligation, or support a legitimate business purpose.
- A pamphlet, better known as the privacy notice. It explains where I’m headed, why I was collected, how I’ll be used, who I might visit, and what rights the traveler has along the way.
✈️ Travel Tip: Don’t issue a ticket unless the destination and purpose are clear and documented.
Security
When I land, I don’t just wander in. I’m protected in transit by encryption, screened by validation checks and filters, and kept away from bots trying to sneak in beside me and other unsavory hitchhikers.
Before most people can access me, they have to authenticate, often using multi‑factor authentication (MFA). Even on vacation, I don’t let just anyone flip through my travel journal.
Security also controls my routing. If the maps are wrong or permissions are misconfigured, I might end up in the wrong system or in front of the wrong audience. That’s how a scenic tour turns into a compliance headache.
✈️ Travel Tip: Strong controls won’t fix a bad map, but they can stop detours from turning into disasters.
The Luggage Carousel
Now I’m circling the luggage carousel. I’ve landed in databases, file storage systems, analytics platforms, and cloud services. I’ve been copied for performance, backed up for disaster recovery, and replicated so systems don’t grind to a halt.
Backups are like souvenir photos, hard to delete or throw away. Necessary, but risky when they pile up. I don’t need fifty shots of the same landmark, but I can’t bring myself to delete any copies. Anything stored forever eventually becomes a liability.
✈️ Travel Tip: Backups are necessary souvenirs. Keep only the ones you can justify later.
The Souvenir Shop
As I travel, I pick up a few additional souvenirs along the way, some of them from organizations I don’t even recall having visited.
Marketing tags me with my industry and inferred interests. Fraud prevention attaches risk scores. Analytics attaches IDs that allow them to link my current trip to all my past journeys.
I started as a simple email address. Now I’ve got a full biography.
This happens through record linkage (often called identity resolution), where systems decide that separate records all belong to the same person. When it works, it reduces duplication and improves service. When it doesn’t, unrelated travelers get stitched together into one very confused identity.
✈️ Travel Tip: The more you enrich data, the harder it is to explain why you needed it.
The Tour Bus
From there, I hop on the tour bus to visit common destinations: Marketing, Sales, Finance, Support, Security.
Each stop has a purpose—but not everyone needs my full itinerary.
Role‑based access and least‑privilege controls help ensure each department sees only what it needs for its stop on the tour, and nothing more.
✈️ Travel Tip: Not everyone needs the full itinerary. Most people just need their stop.
The Side Quest
No trip is complete without a side quest, and a few more stamps on the passport!
I hitch rides to several third-party destinations: payment processors, analytics vendors, support chat tools, cloud providers, and strategic partners. Organizations usually set the ground rules for those detours through vendor agreements, but the trip still needs a clear purpose and appropriate safeguards.
Sometimes, though, I end up on an unscheduled layover: a shadow IT tool, a forgotten integration, a spreadsheet uploaded to the wrong place. That’s when “just this once” becomes incident response.
✈️ Travel Tip: If you don’t know a vendor has your data, that’s not outsourcing—it’s wandering.
✈️ Travel Scenarios to Watch (Sidebar)
- Cross‑border travel: Sometimes I cross borders. Different destinations have different rules, and some trips require extra safeguards.
- Re‑identification risk: I might be labeled “de‑identified,” but when datasets get combined, patterns emerge.
The Postcard Home
As a frequent traveler, I love sending postcards back home.
Organizations summarize data in dashboards, KPIs, trend reports, and cohort analyses, which are all postcards from my journey. To run the analysis, those organizations often aggregate data or try to de‑identify it. Aggregated data has been collected and compiled from multiple sources or individuals to present summary analysis. De-identified data refers to data that has had personal identifiers removed, which reduces linkability. While de-identified data makes it difficult to know who the data refers to, it is not necessarily anonymous, but rather pseudonymous. Pseudonymization swaps names for codes, but the map back still exists somewhere. I can send a postcard home without my name, but my story and patterns are still traceable. By combining a few datasets, de-identified data can become recognizable. Even anonymous postcards can reveal the traveler if you know what to look for. All of these can be useful. None are risk‑free.
✈️ Travel Tip: Before sharing insights, ask whether an individual could still recognize themselves in the story.
The Lost and Found
Every trip has a few bumps. Sometimes data ends up where it’s not supposed to go. Misaddressed emails. Over‑broad exports. Exposed links. Credentials left behind. Data sometimes ends up being shipped off to unexpected persons, places, or things.
✈️ Travel Tip: The best travel agencies prevent these mishaps with least privilege access, encryption, monitoring alerts, careful logs, and regular audits. Incidents often trace back to “temporary” sharing that became permanent.
The Return Ticket
At last, it’s time for me to head home! I’ve traveled extensively through the organization, and I’ve left traces behind everywhere.
Travelers often have rights to track my journey and ask what data was collected, where I went, to ask for corrections, to limit certain uses, opt out of certain kinds of processing, or ask for deletion so that parts of the trip be erased, depending on what geography I originated from.
Deletion isn’t simple. I’ve left footprints in backups, logs, caches, vendor systems, and likely in every other place I traveled. Coordinating deletion from all those points is like rebooking the travel home on six different connecting flights, some might get missed along the way, and only if the agency knows everywhere I’ve been.
✈️ Travel Tip: Data is easiest to delete when you know everywhere it’s traveled.
Landing the Plane
After being a road warrior, I’ve learned the secret to a great trip:
- Collect less.
- Keep the journey short.
- Share intentionally.
- Avoid surprise detours.
- Be honest about the itinerary (purpose of collection).
Before you go, your Monday‑Morning Travel Checklist
- Know what data you collect and where it goes
- Minimize what you carry, and how long you keep it
- Match access to purpose, not curiosity
- Inventory vendors and integrations (including the forgotten ones)
- Make the return trip possible before the journey starts
The best data strategy isn’t faster travel. It’s fewer trips, clearer routes, and easier returns.
Dear Diary,
Today, I traveled less. I slept in a secure, encrypted database and woke up knowing exactly where I’d be tomorrow.
Best trip ever!
| Personal vs. Sensitive vs. De-Identified Data (What’s the Difference?) Think of these as three different travel classifications, not three levels of importance. Personal Data – The Standard Ticket Personal data is any information that relates to an identifiable individual, directly or indirectly. Examples – Name, email address, phone number – Customer or account ID – IP address or device identifier – Online activity associated with a person Key Point: If data can reasonably be linked back to a person, even indirectly, it’s personal data. This is the baseline category most privacy rules are built around. Sensitive Data – Extra Screening Required Some laws identify certain types of personal data as sensitive, which triggers stricter handling expectations. Common examples (vary by law) – Health or medical information – Biometric identifiers – Precise geolocation – Government ID numbers – Children’s data – Information revealing race, religion, or similar traits Key Point: “Sensitivity” isn’t universal. Different laws draw the line differently—but sensitive data almost always comes with tighter limits on use, access, and sharing. |
| De-identified (or Pseudonymized) Data – Masks, Not Invisibility Cloaks De‑identified data is intended to reduce the ability to link information back to a person. Pseudonymized data replaces direct identifiers with a code, but someone still holds the map. Examples – Email replaced with a random user ID – Names removed but behavior patterns retained – Aggregated reports summarizing groups, not individuals Key Point: De‑identified doesn’t mean “risk‑free.” When datasets get combined or mapped back, identity can re‑emerge. The privacy risk depends on context, controls, and safeguards, not just labels. Note: – All sensitive data is personal data. – Most de‑identified data starts as personal data. – Privacy risk depends on where the data travels, not just how it’s described. |
