Using Labels in BigQuery

UpdatedMarch 2, 2026

•1 min read

Using Labels in BigQuery

Constantin Lungu

Senior Data Engineer • Contractor / Freelancer • GCP & AWS Certified

Part of seriesData Ops

🔍 What exactly are BigQuery Labels? They're key-value pairs that you can associate with different BigQuery resources like datasets, tables, views, and even jobs within a session. Consider them as 'tags' that streamline the organization, tracking, and management of your resources.

In the examples shared, we demonstrate how to label BigQuery jobs within a query and then fetch them using the INFORMATION_SCHEMA . JOBS view.

🌟 Wondering about how is it useful?

1️⃣ Expense Breakdown - With labels, you can categorize your BigQuery
expenses by department, project, or any other segment, promoting clear billing.

2️⃣ Efficient Resource Handling - Recognize and handle resources based on their labels, facilitating a tidy and systematic workspace.

3️⃣ Streamlined Automation - Pair labels with Cloud Functions or other GCP tools to automate tasks based on specific labeled criteria.

If you haven't explored labels in BigQuery yet, I urge you to do so. They offer a straightforward approach to instill organization and transparency in your data workspace.

Enjoy your data exploration! 📊

Found it useful? Subscribe to my Analytics newsletter at notjustsql.com.

Comments

Join the discussion

No comments yet. Be the first to comment.

Data Ops

Part 7 of 10

Hands-on guides to data tooling, infrastructure, and operations — scheduling, pipelines, access control, and the engineering behind data workflows.

Scheduled queries in BigQuery

What are Scheduled Queries? Scheduled Queries in BigQuery allow users to run SQL tasks on a predefined, automated schedule. Instead of manually initiating a query each day or week, BigQuery can do it for you. This is perfect for light orchestration o...

More from this blog

BigQuery Saves Your Query Results — Here's How to Find Them

Ever run a heavy BigQuery SQL query, processed gigabytes of data — and then accidentally closed the tab or forgot to save the results? 😬 Don't re-run it. Your results are still there. BigQuery automa

Mar 5, 20261 min read

BigQuery Saves Your Query Results — Here's How to Find Them

Parameters in BigQuery

You can use query parameters in BigQuery hashtag#SQL (now in the console as well!) — but how are they different from variables, and when should you use each? Both parameters and variables act as place

Feb 7, 20261 min read

Parameters in BigQuery

Flattening JSON arrays in BigQuery

I've noticed that a new JSON function has been added (in Preview) in BigQuery SQL - JSON_FLATTEN(). It allows us to flatten JSON arrays and return a single flat ARRAY, no matter how many nested levels there are. So where is this actually useful?➡️ Ha...

Dec 7, 20251 min read

Flattening JSON arrays in BigQuery

Using LAST_VALUE with STRUCTS

Even an “empty” STRUCT is still technically something. Not the same as a standalone NULL value. This is why, if you work with STRUCTs in SQL and try to find the latest non-empty struct using LAST_VALUE(...) IGNORE NULLS, you’ll notice it doesn’t help...

Oct 5, 20251 min read

Using LAST_VALUE with STRUCTS

Table grain quick validation with SQL

I was doing some exploratory data analysis on a number of tables I didn’t have much information about and, unfortunately, didn’t know their grain. I needed a quick way to validate my assumptions about the table grain, identify contradicting observati...

Oct 4, 20251 min read

Table grain quick validation with SQL

D

Datawise: A blog on SQL, BigQuery, Analytics, Python Tips and Tricks

204 posts

Data Engineer with a passion for transforming complex data landscapes into insightful stories. Here on my blog, I share insights, challenges, and the ever-evolving dance of technology and business.