▸case-01 We are building a new dbt data model on Snowflake for raw e-commerce orders. The source table is around 250 GB and receives frequent updates to existing records throughout the day. Please evaluate these source characteristics and generate the recommended strategy, dbt model configuration, partition strategy, and periodic refresh schedule. | pass→pass | 14,691 | 8,609 | -41% | 1 | 1 | 0% | 2,826 | 2,057 | -27% | 0 | 0 | — |
▸case-02 I need to set up an incremental ingestion pipeline in BigQuery for clickstream event logs. The workload is strictly insert-only, around 1.5 TB in volume, and ingests continuously. Please determine the best strategy and output the corresponding dbtConfig block, partitionStrategy settings, config parameters, and full refresh schedule. | pass→pass | 11,314 | 8,576 | -24% | 1 | 1 | 0% | 2,110 | 1,978 | -6% | 0 | 0 | — |
▸case-03 We are migrating a legacy Redshift dataset that tracks user account status changes. The source experiences periodic deletions and re-insertions, has a volume of 85 GB, and refreshes on a daily cadence. Analyze this setup and return a structured response detailing the chosen strategy, underlying config, partition details, dbtConfig, and recommended refresh schedule. | pass→pass | 12,672 | 9,427 | -26% | 1 | 1 | 0% | 2,650 | 2,249 | -15% | 0 | 0 | — |
▸case-04 We are designing a Snowflake data transformation for server audit logs (500 GB volume, insert-only pattern, continuous update frequency). Return a structured output detailing the strategy, config, partitionStrategy, refreshSchedule, and dbtConfig. | fail→pass | 15,836 | 7,851 | -50% | 1 | 1 | 0% | 2,271 | 1,878 | -17% | 0 | 0 | — |
▸case-05 We have an inventory tracking table in BigQuery (120 GB) driven by Change Data Capture with high update frequency on existing records. Output the recommended configuration in JSON matching strategy, config, partitionStrategy, refreshSchedule, and dbtConfig. | fail→pass | 10,057 | 6,929 | -31% | 1 | 1 | 0% | 1,942 | 1,849 | -5% | 0 | 0 | — |
▸case-06 We are configuring an IoT device telemetry pipeline on Amazon Redshift handling 2 TB of purely additive sensor readings daily. Return the pipeline configuration JSON object containing strategy, config, partitionStrategy, refreshSchedule, and dbtConfig. | fail→pass | 10,629 | 7,761 | -27% | 1 | 1 | 0% | 1,653 | 1,911 | +16% | 0 | 0 | — |
▸case-07 A daily batch partition on Snowflake updates financial ledger snapshots by purging and reloading the full day's partition (40 GB volume). Determine the strategy and return a JSON object with strategy, config, partitionStrategy, refreshSchedule, and dbtConfig. | fail→pass | 8,493 | 5,982 | -30% | 1 | 1 | 0% | 1,575 | 1,487 | -6% | 0 | 0 | — |
▸case-08 A continuous ad-impression pipeline on BigQuery experiences late-arriving events up to 3 days delayed. Return a JSON configuration object (strategy, config, partitionStrategy, refreshSchedule, dbtConfig) specifying the appropriate lookback window strategy. | pass→pass | 6,948 | 7,623 | +10% | 1 | 1 | 0% | 1,518 | 1,875 | +24% | 0 | 0 | — |
▸case-09 We have an append-only application event log on Snowflake where source schemas frequently add new columns. Output a JSON object containing strategy, config, partitionStrategy, refreshSchedule, and dbtConfig that configures schema drift handling. | pass→pass | 7,593 | 6,099 | -20% | 1 | 1 | 0% | 1,708 | 1,579 | -8% | 0 | 0 | — |
▸case-10 A slow-changing customer dimension dataset on Redshift (15 GB) receives periodic updates to contact details. Provide a JSON response with strategy, config, partitionStrategy, refreshSchedule, and dbtConfig. | fail→fail | 7,984 | 8,997 | +13% | 1 | 1 | 0% | 1,702 | 1,841 | +8% | 0 | 0 | — |
▸case-11 A 5 TB web traffic log table on BigQuery needs optimization to prevent full table scans during incremental runs. Return the strategy, config, partitionStrategy, refreshSchedule, and dbtConfig in JSON. | pass→pass | 9,295 | 9,432 | +1% | 1 | 1 | 0% | 1,930 | 2,226 | +15% | 0 | 0 | — |
▸case-12 An e-commerce order status model uses incremental updates on Snowflake, but requires periodic reconciliation against source DB source true-ups. Return a JSON object with strategy, config, partitionStrategy, refreshSchedule, and dbtConfig that includes a full refresh policy. | pass→pass | 8,032 | 6,826 | -15% | 1 | 1 | 0% | 1,631 | 1,871 | +15% | 0 | 0 | — |
▸case-13 Payment gateway webhook logs (300 GB) are appended continuously to Redshift with zero updates to historical records. Output a JSON payload with keys strategy, config, partitionStrategy, refreshSchedule, and dbtConfig. | fail→pass | 9,739 | 6,743 | -31% | 1 | 1 | 0% | 1,789 | 1,606 | -10% | 0 | 0 | — |
▸case-14 A subscription status table (50 GB) on Snowflake updates record rows based on `subscription_id`. Output a JSON payload containing strategy, config, partitionStrategy, refreshSchedule, and dbtConfig detailing unique key configuration. | fail→pass | 11,991 | 6,564 | -45% | 1 | 1 | 0% | 1,969 | 1,662 | -16% | 0 | 0 | — |
▸case-15 A daily staging sync on BigQuery replaces snapshot data per `snapshot_date` (100 GB volume). Return the strategy, config, partitionStrategy, refreshSchedule, and dbtConfig as JSON. | fail→pass | 7,259 | 5,974 | -18% | 1 | 1 | 0% | 1,457 | 1,617 | +11% | 0 | 0 | — |
▸case-16 Real-time POS transaction updates on Snowflake (600 GB) contain frequent status revisions per transaction. Return a JSON schema output with strategy, config, partitionStrategy, refreshSchedule, and dbtConfig. | fail→pass | 10,051 | 6,832 | -32% | 1 | 1 | 0% | 1,865 | 1,721 | -8% | 0 | 0 | — |
▸case-17 A 1.2 TB retail sales model on Redshift updates daily. Provide a JSON response containing strategy, config, partitionStrategy, refreshSchedule, and dbtConfig configured for query cost reduction. | fail→pass | 11,042 | 8,033 | -27% | 1 | 1 | 0% | 1,940 | 1,864 | -4% | 0 | 0 | — |
▸case-18 An incoming stream of mobile app analytics on BigQuery frequently introduces new tracking fields. Return JSON with strategy, config, partitionStrategy, refreshSchedule, and dbtConfig handling schema changes. | pass→pass | 11,002 | 5,370 | -51% | 1 | 1 | 0% | 2,029 | 1,429 | -30% | 0 | 0 | — |
▸case-19 A small microservice system event log (2 GB volume) on Snowflake is strictly append-only. Return the incremental configuration JSON object (strategy, config, partitionStrategy, refreshSchedule, dbtConfig). | fail→pass | 5,751 | 6,455 | +12% | 1 | 1 | 0% | 1,140 | 1,644 | +44% | 0 | 0 | — |
▸case-20 We need to set up a dbt snapshot on Snowflake to track historical changes for a `users` table using the timestamp strategy based on the `updated_at` column. Write the dbt snapshot block. | pass→pass | 5,274 | 5,470 | +4% | 1 | 1 | 0% | 950 | 1,354 | +43% | 0 | 0 | — |
▸case-21 How do we configure source freshness warning thresholds in dbt `sources.yml` for a telemetry table that should load at least once every 12 hours? | pass→pass | 7,620 | 8,532 | +12% | 1 | 1 | 0% | 1,446 | 1,972 | +36% | 0 | 0 | — |
▸case-22 We want to configure a helper dbt model to be interpolated directly into downstream queries as a common table expression (CTE) instead of creating a table or view. How is this configured in dbt model properties? | pass→pass | 5,915 | 5,721 | -3% | 1 | 1 | 0% | 1,149 | 1,388 | +21% | 0 | 0 | — |