The first time a software engineer opens the Google Cloud Console, navigates to BigQuery, and creates a dataset, the conclusion seems blindingly obvious. There are datasets. There are tables. There are columns. There is a console where you write standard SQL queries. From a purely visual standpoint, everything looks and feels exactly like a traditional…
Conceptually, migrating between any analytical columnar databases (DWH) looks the same: export data to cloud storage → transfer files → load into the target database → validate. The basic ELT (Extract, Load, Transform) approach remains, but in practice, “the devil is in the details.” AWS and Google Cloud ecosystems have very different tools. Also, the…
Analytics without strict traffic filtering is like trying to calculate airplane aerodynamics while pigeons fly in the wind tunnel. You seem to have data, and charts are drawn, but why does the Cost Per Action (CPA) go through the roof, and the conversion rate stays at the level of a statistical error? We decided to…
Cloud providers love two things: infinite scaling and analysts who don’t know how to use WHERE _PARTITIONTIME. BigQuery works like an all-you-can-eat buffet: you can grab a petabyte of data in a second, but the bill at the end of the month will make your CFO need a strong drink. The cloud does not forgive…
1. What is Dataform Dataform is a Google Cloud tool that helps teams manage data transformations inside BigQuery. It is useful when you have many SQL scripts and want to organize them in one project. With Dataform you can: The main idea: Dataform makes your data pipeline clean, safe, and easy to understand. 2. Basic…
In today’s digital world, data is the most valuable resource for any business. However, collecting, processing, and storing this data can become very expensive and technically complex. This is especially true for projects with high traffic, such as e-commerce platforms or popular mobile applications. When a project generates millions of events every day, using standard…