[DRAFT]ETL 400: Attribute-Level Change Detection in Profile Snapshot Data
Step-by-Step Tracking of Changes:
Daily Snapshot of Data: Every day, you take a snapshot of customer attributes, segment memberships, and identity maps to track changes. You can compute the CRC32 checksum for each table to detect changes.
Tracking Changes in Customer Attributes:
You can create a query to compare the current day’s data with the previous day’s data and identify any changes in customer attributes:
This query compares the CRC32 checksum of the concatenated customer attributes for each customer and checks for differences between today’s and yesterday’s data.
Tracking Changes in Segment Membership:
Similarly, you can track changes in segment membership by comparing the Boolean flags of different segments:
This query tracks changes in segment membership, comparing today’s segment flags to the previous day.
Tracking Changes in Identity Map:
Finally, to track changes in the identity map (email, phone, and loyalty ID):
This query compares the identity information between today and the previous day, tracking any updates in the identity map.
Summary Table of Changes:
You can combine these queries into a single view or summary table that shows the daily changes per customer, across attributes, segments, and identity mappings:
Outcome:
This combined query tracks changes in customer attributes, segment memberships, and identity map on a daily basis. You can use this for reporting, auditing customer data, or triggering specific actions (like personalized marketing updates) based on the detected changes.
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