BigQuery's October 22, 2025 Updates: Your Guide
Hey everyone! 👋 Let's dive into the exciting updates that dropped on October 22, 2025, for BigQuery. We're talking new features, some temporary hiccups, and overall improvements to make your data analysis life easier. I'll break it down so you can easily digest the changes and see how they can benefit you. Get ready to level up your BigQuery game! 🚀
Custom Constraints for Granular Control ⚙️
First up, BigQuery is giving us more control! Now, you can use custom constraints with Organization Policy to fine-tune how you manage specific fields within some BigQuery sharing resources. Think of it as adding extra layers of security and precision to your data sharing. This is a big win for organizations needing strict control over their data exchanges and listings.
So, what does this mean in plain English? Basically, you can set up specific rules that dictate how certain fields behave when sharing data. This level of granularity is super helpful if you need to adhere to compliance regulations, maintain data privacy, or just want tighter control over your data assets. You can ensure that your data is shared in a way that aligns perfectly with your business requirements. This allows for more secure and controlled data sharing, which is particularly beneficial for those dealing with sensitive information or needing to comply with specific industry regulations. You can find more details in the Manage Sharing data exchanges and listings using custom constraints document. Also, keep in mind this feature is currently in preview, so expect some potential changes down the road. It's like a sneak peek at the future of BigQuery's sharing capabilities! Remember, while it's in preview, it's a great opportunity to test it out and get familiar with how it works, but keep in mind that things could evolve.
Key Takeaway: This update empowers you to be more precise with how you share and manage your data, especially within an organization. It's all about providing more granular control over your resources.
Temporary Hiccup: Table Parameters in TVFs 🚧
Now, let's address a temporary snag. Support for table parameters in table-value functions (TVFs) has been temporarily disabled. 😔 The BigQuery team is working hard to bring this feature back as soon as possible, so hang tight! TVFs are powerful tools that let you treat functions as tables, making complex data transformations more manageable. The temporary removal of this feature might impact some of your existing workflows that rely on it. For those of you who frequently use TVFs, this is something to be aware of. You might need to adjust your queries or explore alternative methods until the support is restored. It's like a temporary detour on a well-worn road, but rest assured, the road crew is on the job to get things back to normal! Keep an eye on the BigQuery release notes for updates on when the TVF support will be fully restored. We're all in this together, and hopefully, it won't be too long before we're back to full functionality. While the feature is down, it's a good opportunity to evaluate if you have any other options.
Key Takeaway: Table parameters in TVFs are temporarily unavailable, but the team is actively working on restoring them. Stay tuned for updates!
TimesFM Univariate Time Series Forecasting Model 📈
Alright, let's get to something really cool! BigQuery ML has added a built-in TimesFM univariate time series forecasting model. This is based on Google Research's open-source TimesFM model. Basically, BigQuery can now predict future data points in time series datasets. This is a game-changer for businesses needing to forecast sales, predict demand, or analyze trends over time.
With this update, you can use the AI.FORECAST function for forecasting, which now supports a larger context window, allowing for more comprehensive predictions. You can also use the AI.EVALUATE function to assess the accuracy of your forecasts against historical data. This integration is designed to make time series analysis simpler and more accessible. It’s like having a built-in crystal ball for your data. The TimesFM model is excellent for a wide variety of time series data. You can perform forecasting using the AI.FORECAST function and evaluate forecasted data with the AI.EVALUATE function. It's like having a built-in crystal ball for your data! This is useful for predicting sales, understanding customer behavior, and planning for the future. The AI.FORECAST function now supports a larger context window, which means it can consider a more extensive range of past data when making predictions, potentially leading to more accurate forecasts. You can also evaluate your forecasted data against a reference time series based on historical data using the AI.EVALUATE function, ensuring the model's reliability and precision.
Key Takeaway: BigQuery ML now offers a built-in TimesFM model, making time series forecasting more accessible and powerful. This feature is generally available (GA), which means it's ready for production use!
How to Get Started with TimesFM
To give the AI.FORECAST function with the TimesFM model a try, check out the Forecast a time series with a TimesFM univariate model tutorial. This guide will walk you through the steps to get started with time series forecasting, allowing you to quickly apply the model to your own datasets. It’s a great way to learn and see the power of TimesFM firsthand. This tutorial provides detailed instructions and examples, making it easy to understand and implement. You'll learn how to set up your data, configure the model, and interpret the results. The tutorial makes it easy to get started with time series forecasting and see how it can benefit your business. It allows you to quickly apply the model to your own datasets and see the power of TimesFM firsthand.
Overall Impact and Benefits
These updates are all about enhancing your BigQuery experience. The addition of custom constraints provides you with greater control over your data. TimesFM brings the power of time series forecasting directly into your workflow. Even the temporary hiccup with TVFs will be resolved, ensuring that you can continue to leverage the full capabilities of BigQuery. These improvements are a testament to BigQuery's commitment to continuous improvement. BigQuery is always evolving to meet the needs of its users. Keep an eye out for these improvements and explore how they can enhance your data analysis workflows. Stay updated with the latest releases to make the most of BigQuery's capabilities. These changes showcase BigQuery's ongoing commitment to providing powerful tools for data analysis and management. By keeping up-to-date with these releases, you can leverage the latest features to improve your data analysis workflows. These changes show that BigQuery is staying ahead of the curve in providing you with innovative tools for data analysis.
Thanks for tuning in! I hope this helps you understand the latest BigQuery updates. Keep an eye on future releases for more exciting features! 🤓