[BQML] Completing Missing Values with Gemini Grounding (Google Search)
Published:Dec 25, 2025 09:20
•1 min read
•Zenn Gemini
Analysis
This article discusses using BigQuery ML (BQML) with Gemini and Grounding with Google Search to address the common problem of missing data in data analysis. Traditionally, filling in missing data required external scripts and APIs or manual web searches. The article highlights how this new approach allows users to complete this process using only SQL, streamlining the data completion workflow. This integration simplifies data preparation and makes it more accessible to users familiar with SQL. The article promises to detail how this integration works and its benefits for data analysis and utilization, particularly in scenarios where data is incomplete or requires external validation.
Key Takeaways
- •BQML, Gemini, and Grounding with Google Search can be combined to fill missing data.
- •This combination allows data completion using only SQL.
- •This simplifies the data completion workflow compared to traditional methods.
Reference
“データ分析や活用において、頻繁に課題となるのが 「データの欠損」 です。”