For many data professionals, the most daunting part of a new project isn’t the complexity of the data or the sophistication of the model, it’s the “blank slate.” Staring at an empty notebook while creating a data cleaning pipeline from scratch, or searching for the best way to run time-series forecasting can stall your momentum before the real analysis even begins.
Today, we’re excited to announce the general availability (GA) of the BigQuery Studio notebook gallery. This curated collection of pre-built templates is designed to help you bypass the setup phase and jump straight into discovery.
Quickly browse through the notebook gallery and launch a template with a single click.
Move past the blank slate with curated templates
BigQuery Studio notebooks bring the power of Colab Enterprise directly into the BigQuery UI, providing a smooth transition between SQL-based data prep, Spark-powered processing, and Python-based analysis. The notebook gallery supports this unified experience with templates tailored to different skill sets and objectives.
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For SQL developers: Many users are comfortable with SQL but want to explore the expanded capabilities of a notebook environment. Templates in the gallery demonstrate how to use SQL cells to load data and then use visualization cells for no-code charts, making it easier to share insights without writing extensive Python.
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For data scientists: Python and Spark users can find ready-to-use workflows for data cleaning, transformation, and advanced ML development using BigQuery DataFrames and Spark libraries. These templates follow best practices, so that your code stays efficient and takes full advantage of BigQuery’s distributed engine.
Choose the right template for your project
The gallery is organized to help you find the right starting point for your specific goals, from data analysis and visualization to building advanced data science workflows.
If you’re starting your journey with BigQuery Studio notebooks, the gallery offers several introductory templates:
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Introduction to notebooks in BigQuery Studio: A high-level tour that covers SQL cells, visualization cells, Python-based visualizations, and running AI predictions.
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Getting started for SQL users: A guide for those comfortable with SQL who want to make queries dynamic with Python variables and visualize findings, without writing complex code.
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Getting started for Python users: A workflow focused on using BigQuery DataFrames to clean, merge, and analyze datasets.
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Getting started with Spark: A hands-on guide to launching serverless Apache Spark sessions in BigQuery Studio to join, analyze, and visualize BigQuery data using Spark SQL and Python.
For seasoned notebook users, you can leverage specialized templates to handle complex analytical workflows:
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Generative AI & Multimodal Analysis: Unify structured and unstructured data. Use the Analyze multimodal data in BigQuery template to apply Gemini models to images or audio files and return insights directly as SQL results.
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Machine Learning Development: Accelerate the ML lifecycle with the Exploratory data analysis with BigQuery DataFrames template, which uses BigFrames to perform feature engineering and model training at scale. For distributed workloads, the E-commerce purchase predictions with Apache Spark ML template provides a complete, serverless workflow for training predictive models on BigQuery data.
- Data Pipelines & Transformation: Master data reliability and real-time streaming. Use the Data Quality and Profiling with BigFrames template for cleaning datasets, or the Real Time Data Export to Pub/Sub template for operationalizing data with continuous queries.
The introduction to notebooks template is a great one to open for any new project as it covers the major features of BigQuery Studio notebooks.
Access the gallery in your workflow
You can find the gallery directly in the BigQuery Studio console:
1. From the welcome page: Navigate to the “Welcome to BigQuery Studio” page and click View notebook gallery.
2. From the asset menu: Click the (+) icon to create a new asset, select Notebook, and then choose All templates.
The gallery allows you to filter by task, such as data transformation or predictive analysis, so you can find the specific workflow that matches your goals. When you find the right template, you can open a read-only version to preview it and then click a button to add a copy to your project.
Get started
Open the notebook gallery in BigQuery Studio today to find a template for your next project.
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Open the gallery: Explore the curated collection in the BigQuery console.
- Read the documentation: Learn more about how to use these templates in our official guide.
