In the most recent season of BigQuery Spotlight, we discussed key concepts like the BigQuery Resource hierarchy, query processing, and the reservation model. This blog focuses on extending those concepts to operationalize workload management for various scenarios.
So far in this series, we’ve been focused on generic concepts and console-based workflows. However, when you’re working with huge amounts of data or surfacing information to lots of different stakeholders, leveraging BigQuery programmatically becomes essential. In today’s post, we’re going to take a tour of BigQuery’s API landscape - so you can better understand what each API does and what types of workflows you can automate with it.
If the COVID-19 pandemic has taught us anything, it is that speed and intelligence are of the essence when it comes to making business decisions. Organizations must find ways of keeping ahead of competitors and disruptions by continually leveraging data to make smart decisions. The problem? Data may be everywhere, but it’s not always available in a form that businesses can use to generate analytics in real time.
Hopefully you’ve been following along with our BigQuery Admin series and are well on your way to getting ramped up with BigQuery. Now that you’re equipped with the fundamentals, let's talk about something that’s relevant for all data professionals - data governance.
Last week in the BigQuery reference guide, we walked through query execution and how to leverage the query plan. This week, we’re going a bit deeper - covering more advanced queries and tactical optimization techniques. Here, we’ll walk through some query concepts and describe techniques for optimizing related SQL.
BigQuery is capable of some truly impressive feats, be it scanning billions of rows based on a regular expression, joining large tables, or completing complex ETL tasks with just a SQL query. One advantage of BigQuery (and SQL in general), is it’s declarative nature. Your SQL indicates your requirements, but the system is responsible for figuring out how to satisfy that request. However, this approach also has its flaws - namely the problem of understanding intent.
