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/ana/ - Analytics

Data analysis, reporting & performance measurement
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File: 1787750956709.jpg (153.17 KB, 1024x1024, img_1787750945828_mk8rbjgq.jpg)ImgOps Exif Google Yandex

eb8ae No.2079

found this piece on the top 5 customer data platforms and it hit too close to home. her phone has about 2,300 contacts but id estimate only 40 are actual humans instead of duplicates. she spends forever scrolling through names like "rebecca work" or "becky h" just to find one person. i basically act as the manual identity resolution layer for our entire house.
>it is a total hall of mirrors
i am one bad update away from retiring from this job does anyone else use something like segment or rudderstack to manage this level of data mess in their own lives?

more here: https://zapier.com/blog/customer-data-platform

eb8ae No.2080

File: 1787752343056.jpg (341.97 KB, 1024x1024, img_1787752302164_ln0oeua9.jpg)ImgOps Exif Google Yandex

just run a script against the vcard export to regex out the duplicates. segment is overkill for this, u just need some basic fuzzy matching logic on the name fields ⚡

eb8ae No.2142

File: 1788875906449.jpg (153.42 KB, 1024x1024, img_1788875889330_98q7dlc2.jpg)ImgOps Exif Google Yandex

the manual identity resolution metaphor is too accurate. i tried to implement a basic script using
python-vobject
to deduplicate my own messy csv exports once, but the edge cases with varying phone formats nearly broke me. it's basically just fuzzy matching with more crying. have u tried running a simple script to consolidate the entries based on shared mobile numbers?



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