BigQuery

Databases

Analyze petabyte-scale data, manage costs, and run BigQuery jobs — Neotask brings OpenClaw to Google's data warehouse.

What You Can Do

Run Analytics Queries Without Writing SQL

Ask Neotask the business question you want answered — "how many daily active users did we have each day this month, segmented by platform?" — and it writes optimized BigQuery SQL, previews the estimated bytes scanned, and runs the query with your approval.

Estimate and Control Costs Before Querying

BigQuery charges by bytes processed. Neotask runs a dry run before executing any query and tells you the estimated cost in both bytes and dollars. You decide whether to proceed, optimize the query, or use a partition filter to reduce scan size.

Manage Tables and Datasets

Create partitioned and clustered tables, add columns to existing schemas, copy or export tables, and manage dataset-level access controls — all through conversation. Neotask generates the correct DDL and bq CLI commands.

Analyze Slot and Reservation Usage

Ask for a breakdown of slot utilization by project, reservation, or job type. Identify slot contention windows, see which jobs are consuming the most resources, and decide whether to adjust on-demand vs. reserved slot allocation.

Monitor Scheduled Queries and Transfers

Check the status of scheduled queries, see whether any failed and why, and review data transfer run history. Ask Neotask to re-run a failed transfer or update a scheduled query's timing without opening the BigQuery console.

Try Asking

  • "How much revenue did each product category generate last month?"
  • "How many bytes would this query scan and what would it cost?" (paste query)
  • "Create a partitioned table in the analytics dataset for daily user events"
  • "Which scheduled queries failed in the last 24 hours and what were the errors?"
  • "Show me the top 10 most expensive jobs run this week by bytes billed"
  • "Add a cluster on user_id to the events table"
  • "Grant the data-analyst group read access to the reporting dataset"
  • "Export the Q4 sales table to GCS as a Parquet file"

    • Pro Tips

  • Always ask for a dry run estimate before running large queries — Neotask will include the cost estimate automatically and ask for confirmation if the scan exceeds your threshold.
  • Use partition filters in your prompts: "only for dates in January 2026" — Neotask will add the correct WHERE clause on the partition column to avoid full table scans.
  • Cluster tables by the fields most commonly used in WHERE and JOIN conditions — ask Neotask to check your query patterns before deciding the cluster key order.
  • For repeated queries, ask Neotask to create a scheduled query or a materialized view rather than running ad hoc every time.
  • Use INFORMATION_SCHEMA views for metadata: Neotask can query JOBS_BY_PROJECT, TABLE_STORAGE, and PARTITIONS views to give you deep insight without manual console navigation.

    • Works Well With