When you’re syncing data across tools, bad data isn’t just annoying—it can break automations, mess up reports, and make your team lose trust in the system. If you’re using Syncari, you already know it helps wrangle data between sources. But the real magic is making sure junk data never gets in the door in the first place. That’s where custom data validation rules come in.
This guide is for anyone who wants fewer data headaches—admins, ops folks, or anyone who’s been burned by a bad sync. I’ll show you how to build your own guardrails inside Syncari so you don’t have to clean up messes later.
Why Bother With Custom Validation Rules?
Let’s get real: Out-of-the-box validation rules are fine, but they’re rarely enough. Every team has its quirks. Maybe you have a unique customer ID format, or you want to block demo email addresses (like @gmail.com) from getting into your CRM. Relying on default rules is like locking your front door but leaving the windows open.
Custom validation rules let you:
- Enforce your business logic, not just generic standards.
- Catch errors early, before they snowball.
- Save time (and embarrassment) when data ends up in the wrong place.
If you’re sick of fixing the same mistakes over and over, it’s time to invest a little up front.
Step 1: Map Out What “Bad Data” Means for You
Before you go clicking around Syncari, stop and get clear on what you actually want to prevent. Don’t just copy some generic list. Instead, ask:
- What are the fields that cause the most trouble?
- What patterns or values are unacceptable in your context?
- Are there compliance or business rules you must enforce?
Examples of custom validation needs: - Phone numbers must be 10 digits, no letters. - Email can’t be a free provider (Gmail, Yahoo, etc.). - “Annual Revenue” must be a positive number. - Date fields can’t be in the future.
Write these down somewhere. You’ll use this as your checklist.
Pro Tip: Don’t try to boil the ocean. Start with your biggest pain points. You can always add more rules later.
Step 2: Get to Know Syncari’s Validation Options
Syncari lets you set up validation rules within its Data Studio, mostly via “Field Policies” and “Validation Rules.” Here’s what you need to know:
- Field Policies: Basic guardrails (required fields, type enforcement, allowed values).
- Validation Rules: More advanced, using expressions or even scripts for complex logic.
You’ll find these by opening a Synapse or Unified Data Model in Data Studio, then drilling into the field settings.
What works: Field Policies are fast to set up and handle 80% of needs. Validation Rules give you more power, but require a bit more logic know-how.
What doesn’t: Don’t expect Syncari to fix all bad data with one click. Upstream systems and bad integrations can still sneak stuff through. This is a filter, not a silver bullet.
Step 3: Create Field Policies for the Basics
- Open Data Studio in Syncari.
- Navigate to your Unified Data Model (UDM) or the specific Synapse (your connected source).
- Click on the object/table you want to protect (e.g., “Leads”).
- Click into the field you want to validate (e.g., “Email”).
- Under the Policies tab, set:
- Required: Should this field always have a value?
- Data Type: Is this a string, number, date, etc.?
- Allowed Values: For picklists or status fields.
Example:
For a “Status” field, set allowed values to “Open,” “Closed,” and “Pending.” This stops typos or bad entries from slipping through.
Caveat: Field Policies won’t catch things like “bob@@gmail..com” as an invalid email. They’re good for the basics, but not for patterns or cross-field logic.
Step 4: Build Custom Validation Rules for Your Edge Cases
This is where you catch the tricky stuff—formatting, value ranges, or rules that depend on multiple fields.
- In the Data Studio, go to the field you want to validate.
- Look for the Validation Rules or Field Expressions section.
- Add a new rule. You can write simple expressions or, if needed, use Syncari’s expression language (which is pretty close to Excel formulas).
Common validation examples:
- Email format:
REGEX_MATCH(Email, "^[\w\.-]+@[\w\.-]+\.\w+$")
Returns true only if email matches the pattern.
- No free email providers:
NOT(REGEX_MATCH(Email, "@(gmail|yahoo|hotmail)\.com$"))
Blocks common free domains.
- Phone number length:
LENGTH(Phone) = 10
Makes sure phone numbers are 10 digits.
Pro Tip: Test your expressions with real data. A rule that’s too strict could block legit records. A rule that’s too loose won’t help at all.
What to ignore: Don’t get carried away with edge cases that rarely happen. Focus on the errors that actually cost you time.
Step 5: Set Up Error Handling and Notifications
Validation is only half the battle—you also need to know when something goes wrong.
- Configure validation error handling: Decide if you want Syncari to block the record, skip it, or just flag it.
- Set up notifications: Use Syncari’s built-in alerting or connect to Slack/Email via a webhook, so you’re not left guessing.
Reality check: If you don’t monitor your validation failures, you’re back to square one. It’s easy to set up an alert and ignore it forever. Make sure someone’s actually checking.
Step 6: Test, Iterate, and Don’t Overcomplicate It
Once your rules are in place, run a test sync with sample data. Look at the error logs. Are your rules catching the right things? Are they too strict?
- Review the error messages. Are they clear? Will someone else know what to do?
- Add exceptions where needed (e.g., allow internal test emails).
- Tweak as you go. Data changes, and so will your rules.
Pro Tip: Keep an eye out for false positives (legit data getting blocked) and false negatives (bad data slipping through). No rule is perfect on the first try.
What Works, What Doesn’t, and What to Skip
Works well: - Catching obvious mistakes (wrong formats, missing required fields). - Blocking known bad patterns (free emails, test data). - Enforcing picklist values.
Doesn’t work as well: - Complex cross-object logic (e.g., “If Account is in X region and Lead Score > 75, then...”). - Cleaning up data that’s already wrong in upstream systems (Syncari can block it, but can’t fix it).
What to skip: - Overly complex validations that are hard to explain or maintain. - Trying to solve business process problems with validation rules alone.
Keep It Simple and Iterate
Most data problems are death by a thousand cuts. Set up the basics, watch for what keeps breaking, and add new rules as you go. Syncari makes it easy to adjust—don’t try to get it perfect on day one.
Data quality isn’t glamorous, but a few smart validation rules can save you hours of cleanup (and a lot of cursing at spreadsheets). Start small, stay practical, and make sure someone’s watching the alerts. That’s how you actually keep errors out—no hype required.