--- title: Data Classification for Google BigQuery - Predicting Cost description: cost of data classification smart sampling for google big query --- [Skip to content](https://docs.mineos.ai/knowledge/cost-for-bigquery-integration#main-content) [![Mine](https://docs.mineos.ai/hs-fs/hubfs/Frame%201948756858.png?width=62&height=40&name=Frame%201948756858.png)](https://docs.mineos.ai/knowledge) Open main navigation Close main navigation Hello! How can we help you? - There are no suggestions because the search field is empty. 1. [Help center](https://docs.mineos.ai/knowledge) 2. [Integrations](https://docs.mineos.ai/knowledge/integrations) # Data Classification for Google BigQuery - Predicting Cost ## Understand cost involved with running data classification on BigQuery Datasets   Notes - The cost described in this article is cost associated with your GCP account, and not the cost for MineOS subscription. - The information below applies to BigQuery tables, and not views.   **How MineOS Smart Sampling Works with Google BigQuery** MineOS uses a **smart sampling** approach to classify data in your BigQuery environment efficiently. Rather than scanning entire datasets, we analyze a statistically representative sample of each table to identify data types (PII, PHI, PCI, GDPR special categories, etc.) while minimizing query costs.   **Key Features:** - **Project-level scanning:** Classification is configured at the BigQuery Project level for comprehensive coverage - **Statistical sampling:** We use proven statistical formulas to determine the minimum sample size needed to accurately represent your entire dataset - **Cost-optimized queries:** Our approach is specifically designed to minimize BigQuery processing costs **Understanding BigQuery Costs** BigQuery charges are based on the **number of bytes processed** (billed bytes), not the number of rows returned. This means: - Minimum billing: 10MB per query - Block-based processing: BigQuery processes data in memory blocks (typically ~64MB each) - Cost is determined by how many blocks are scanned, not how many rows are examined **MineOS Cost Control Mechanisms** We've implemented multiple safeguards to keep your BigQuery scanning costs predictable and minimal: 1. **Metadata-First Approach** We retrieve table row counts from BigQuery metadata rather than running expensive `COUNT(*)` queries, eliminating unnecessary data processing. 2. **Block-Aware Optimization** Our sampling logic is optimized for BigQuery's memory block architecture, calculating the most efficient sample percentage to avoid processing mostly empty blocks while maintaining statistical accuracy. 3. **Percentage-Based Table Sampling** We use BigQuery's `TABLESAMPLE` function with calculated percentages. For example, if we need to sample 20% of a table, BigQuery processes approximately 20% of memory blocks rather than the full dataset. **Note:** If your tables use partitioning, costs may be slightly higher since memory blocks cannot span multiple partitions. Tables with many small partitions may require scanning more blocks than non-partitioned tables of the same size. 4. **Hard Cap Protection** In sampling, we enforce a maximum limit on processed bytes per table (2TB). If this threshold is approached, the query is automatically canceled at zero cost, preventing unexpected billing spikes. 5. **Sample Size Limits** We apply maximum row caps per table based on statistical relevance, ensuring we never process more data than necessary for accurate classification.**Cost Transparency & Estimates** **Typical Cost Profile:** For most BigQuery environments, smart sampling costs are **minimal compared to full data scans**: - **Small tables** (\<1GB): Often fall under the 10MB minimum, resulting in negligible costs - **Medium tables** (1-100GB): Sampling typically processes 1-5% of total data - **Large tables** (\>100GB): Smart sampling processes a statistically valid subset, often \<1% of total data. **Example:** - Full table scan of 1TB table: ~$5 USD (processing 1TB) - MineOS smart sample of same table: ~$0.05-0.25 USD (processing 10-50GB sample) **Best Practices for Cost Management** 1. **Start with a subset:** Test classification on a few tables or a single project before scaling to your entire BigQuery environment 2. **Review table metadata:** Ensure unnecessary or archived tables are excluded from scanning scope 3. **Monitor BigQuery billing:** Track actual costs in your GCP console during and after scanning 4. **Leverage partitioned tables:** While partitioning doesn't reduce our sampling costs directly, it helps organize data for more targeted classification scopes 5. **Contact support:** If you have concerns about specific large tables or cost thresholds, reach out to our team—we can adjust sampling parameters for your environment **Frequently Asked Questions**   **Q: Will I be charged for the BigQuery queries MineOS runs?** Yes, BigQuery queries initiated by MineOS will appear in your GCP billing under your project. However, our smart sampling approach minimizes these costs significantly compared to full table scans.   **Q: Can I set a budget limit for classification costs?** Yes, we can work with you to define acceptable cost thresholds and adjust scanning scope accordingly. Our 2TB per-table hard cap provides automatic protection against runaway costs.   **Q: How often does classification need to run?** Smart sampling is typically a one-time or periodic activity (quarterly/annually), not continuous. Once data types are classified, you only need to re-scan when significant schema or data changes occur.   **Q: What if I have very large tables (multi-TB)?** Our hard cap protection prevents processing more than 2TB per table. For extremely large tables, we recommend reviewing sampling parameters with our team to balance cost and classification accuracy.   ### **Enable Preview mode** To view sample PII values alongside classification results. The sample values are stored encrypted and automatically deleted after 7 days. You must enable Preview mode before running the scan to see sample values. For more information about how to set up Preview mode go [here](https://docs.mineos.ai/knowledge/data-classification-preview-mode). - [Data Inventory](https://docs.mineos.ai/knowledge/data-inventory#main-content) - [Systems](https://docs.mineos.ai/knowledge/data-inventory#systems) - [Data types](https://docs.mineos.ai/knowledge/data-inventory#data-types) - [Activities](https://docs.mineos.ai/knowledge/data-inventory#activities) - [Compliance Operations](https://docs.mineos.ai/knowledge/compliance-operations#main-content) - [Compliance reports](https://docs.mineos.ai/knowledge/compliance-operations#compliance-reports) - [Policies & alerts](https://docs.mineos.ai/knowledge/compliance-operations#policies-alerts) - [Risk assessments](https://docs.mineos.ai/knowledge/compliance-operations#risk-assessments) - [DSR Handling](https://docs.mineos.ai/knowledge/dsr-handling#main-content) - [Setting Up Channels](https://docs.mineos.ai/knowledge/dsr-handling#setting-up-channels) - [Configuring Responses](https://docs.mineos.ai/knowledge/dsr-handling#configuring-responses) - [Processing Requests](https://docs.mineos.ai/knowledge/dsr-handling#processing-requests) - [Audit & Reporting](https://docs.mineos.ai/knowledge/dsr-handling#audit-reporting) - [Setting Up Rights & Workflows](https://docs.mineos.ai/knowledge/dsr-handling#setting-up-rights-workflows) - [Integrations](https://docs.mineos.ai/knowledge/integrations#main-content) - [General information](https://docs.mineos.ai/knowledge/integrations#general-information) - [Settings & Security](https://docs.mineos.ai/knowledge/settings-security#main-content) - [Security](https://docs.mineos.ai/knowledge/settings-security#security) - [Your Account](https://docs.mineos.ai/knowledge/settings-security#your-account) - [Developers Documentation](https://docs.mineos.ai/knowledge/developers-documentation#main-content) - [Portal for developers](https://docs.mineos.ai/knowledge/developers-documentation#portal-for-developers) - [Webhook](https://docs.mineos.ai/knowledge/developers-documentation#webhook) - [Other](https://docs.mineos.ai/knowledge/developers-documentation#other) - [Release Notes](https://docs.mineos.ai/knowledge/release-notes) - [Consent Management](https://docs.mineos.ai/knowledge/consent-management) [![Frame 1948756858](https://docs.mineos.ai/hs-fs/hubfs/Frame%201948756858.png?width=62&height=40&name=Frame%201948756858.png "Frame 1948756858")](https://mineos.ai/) Copyright © 2026, "MineOS" (Saymine Technologies Inc)