![rw-book-cover](https://images.unsplash.com/photo-1553729459-efe14ef6055d?crop=entropy&cs=tinysrgb&fit=max&fm=jpg&ixid=MnwxMTc3M3wwfDF8c2VhcmNofDN8fG1vbmV5fGVufDB8fHx8MTY1NjAwNTU1Nw&ixlib=rb-1.2.1&q=80&w=2000content/images/size/w1200) ## Metadata - Author: [[narrator-data-blog|Narrator Data Blog]] - Full Title:: The Cost of Product Analytics Data in Your Data Warehouse - Category:: #🗞️Articles - Document Tags:: [[Product analytics and sequence analytics|Product Analytics And Sequence Analytics]], - URL:: https://www.narratordata.com/blog/the-cost-of-product-analytics-in-you-warehouse/amp/ - Finished date:: [[2023-12-28]] ## Highlights > The questions that you want to answer–*what was the last paywall before a purchase, which campaign led to an order, etc...–*become very complex queries. No BI tool (i.e. Looker, Tableau, etc...) has been able to solve this problem. ([View Highlight](https://read.readwise.io/read/01hjpmkff7f87xst9s4nhzhwv3)) > **Identity needs to be resolved across multiple systems** - A user in your product analytics table is difficult to match to the user in your internal systems. This is such a complex problem that there are many companies ([intricity for example](https://www.intricity.com/learningcenter/intricity-identity-resolution-powered-by-snowflake?ref=www.narratordata.com/blog)) that exist solely to stitch the anonymous user cookie to your internal identifier. ([View Highlight](https://read.readwise.io/read/01hjpmmbrw869a7zj5tbnt7v8w))