Get all unique Firebase Analytics events in BigQuery

As I mentioned in my earlier post about the drawbacks with the entity-attribute-value data model used in Firebase Analytics and Google Analytics app plus web, it is hard to know what events and associated attributes and data types are logged without proper documentation. Another way to get an overview is to actually query the table. Below you find an example of how to do it. SELECT event_name, ARRAY_AGG(struct(name, value)) as attribute FROM( SELECT event_name, param. »

Why Google Analytics App + Web BigQuery Export Rocks and Sucks

Google recently released Google Analytics App + Web which essentially is something like Firebase Analytics for web (or Google Analytics version 2 if you want to). This is exciting for many reasons, two of them are: Google is finally moving away from a user-session-pageview based model to one built on users and events It supports BigQuery export also for standard users That is awesome. These two are actually two of the primary reasons why I built datahem. »

Configure Firebase Analytics and Google Analytics app + web Bigquery export to EU region

January 2019 when I tried to set up BigQuery export on our Firebase Analytics projects I found out that I couldn’t chose region for the export and that it defaults to US. Since my employer is an European comapny I prefer to store the data in EU. This is the exact same issue that I had previously with GA360 BigQuery Export and I thought I would try to solve it in a similar manner (that has become part of the the GA360 BigQuery Export documentation for how to geolocate your data in EU). »

Fast and flexible data pipelines with protobuf schema registry

MatHem is growing quickly and so are the requirements for fast and reliable data pipelines. Since I joined the company a little more than one year ago I’ve been developing an event streaming platform (named DataHem) to meet those requirements. 1 Background Before jumping into the solution architecture, I thought I would give you some background from a business perspective that has influenced the design choices. 1.1 Context MatHem is the biggest online grocery store in Sweden and to briefly give a context this is how the business works: »

Bigquery efficient access management

A strategic decision we’ve made at MatHem is to enable users to connect to or data warehous (BigQuery) with whatever tool (tableau, data studio, collab, etc.) they prefer and still be certain that they only can access data that they have permission to. That turned out to be a challenge in BigQuery with the current access management capabilities, since you give users/roles (or authorized views) access on the dataset-level and not views/table-level. »