Troubleshooting Data Discrepancies | Stitch Documentation

Data discrepancies can surface as missing records, incorrect values, or fields not being correctly typed. If something in your data warehouse doesn’t look quite right, these resources will help you get to the root of the problem.

Places to start

Pinpointing the cause of a data discrepancy has the potential to require quite a bit of investigation. To increase efficiency, we recommend using these three resources to perform quick checks on some of the more obvious and common causes.

Data Discrepancy Troubleshooting Guide If you’ve noticed missing or incorrect data in your destination, this guide is the place to start. In it we’ll walk you through the most common causes of data discrepancies, how to verify the root cause, and how to fix it. We also outline the next steps should you need to contact support.

Known Third-Party Issues Occasionally, some integrations used by Stitch may encounter bugs or other issues. Whenever we’ve identified a third-party issue - meaning on the integration provider’s end - we’ll post an update here.

Third-Party Integration Downtime From time to time, some of the applications and databases we integrate with may experience downtime. During these outages, Stitch may be unable to successfully connect to your data source and replicate your data.

Additional resources

Database Integration Table Name Collisons In database integrations, if the names of multiple tables canonicalize to the same name - even if they’re from different source databases or schemas - name collisions and data discrepancies can occur. This applies to any database integration available in Stitch.

Missing Columns & NULL Values If you’ve noticed some missing columns or data from your data warehouse, the root cause may be NULL values.

Missing Mongo Data Due to Fields with Multiple Data Types Missing some Mongo data? The root cause may be multiple data types in the Replication Key or Primary Key (_id) fields.

Missing Segment Data & Selective Integration Snippets If you’ve noticed some missing data from your Segment integration, the culprit might be the selective integration snippet on your website.

Mongo Fields Missing from Replication Key Menu If you don’t see all the fields you expect to in the Replication Key field for you Mongo integration, the root cause may be insufficient permissions or a lack of field indexing.

MySQL TINYINT(1)/boolean Columns Stored as BIT If you’ve noticed that some MySQL TINYINT(1) columns are displaying as BIT in Stitch, it’s usually due to how the MySQL driver converts this data type.

Non-Replicating Data & Unsupported Data Types If a table isn’t replicating into your data warehouse, it may be because one or more of the columns in the table contains an unsupported data type.

PostgreSQL Read Replicas and Slow Replication If you connected a PostgreSQL read replica as a database integration and are experiencing extremely slow replication, the root cause may be the database’s standby settings.

Stale Salesforce Data & Formula Fields If you’ve noticed some out-of-date Salesforce data in your data warehouse, the root cause may be a formula field.