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Design an approved incident destination for failed job events. This design action addresses a different case (job webhook destination), where only personal email notifications are configured. Supported job notification destinations can integrate workflow status with an incident system. In the stated problem, a manual UI report omits failed tasks and paginated runs; this choice would not establish the required jobs rest monitoring decision.

Report violation rate as an explicit quality indicator. This design action addresses a different case (expectation monitoring), where analysts confuse successful pipeline status with zero rejected records. Quality metric events reveal input and dropped records separately from update status. In the stated problem, a manual UI report omits failed tasks and paginated runs; this choice would not establish the required jobs rest monitoring decision.

Design a governed cost dashboard grouped by job/workload labels. This design action addresses a different case (billing usage monitoring), where cost reports omit some job and workspace labels. Databricks system billing tables can expose usage records for cost attribution. In the stated problem, a manual UI report omits failed tasks and paginated runs; this choice would not establish the required jobs rest monitoring decision.

Run two distinct batches and confirm both histories remain accessible. This validate action addresses a different case (append-only delta bronze), where a nightly overwrite accidentally removes historical audit events. Append-only ingestion keeps previous raw records while adding new batches. In the stated problem, unknown or mismatched fields disappear during the bronze load; this choice would not establish the required auto loader rescued data decision.

Ingest old and new samples and verify nested fields and rescued data are retained. This validate action addresses a different case (nested json ingest), where the initial reader assumes one unchanging flat schema and loses new fields. Explicit schema management and rescued data handling protect evolving semi-structured ingestion. In the stated problem, unknown or mismatched fields disappear during the bronze load; this choice would not establish the required auto loader rescued data decision.

Parse an order with three line items and confirm all three survive. This validate action addresses a different case (xml repeating elements), where an XML ingest incorrectly flattens multiple line items into one text field. XML ingestion must specify the repeating row element and preserve nested structure. In the stated problem, unknown or mismatched fields disappear during the bronze load; this choice would not establish the required auto loader rescued data decision.

Tune shuffle partitions or adaptive coalescing on the affected workload. This implement action addresses a different case (shuffle partition count), where the current partition count is too low for data volume. Shuffle partition sizing affects memory pressure and task parallelism. In the stated problem, the merge scans unrelated historical partitions; this choice would not establish the required predicate-limited merge decision.

Enable Photon on the selected supported warehouse or compute. This implement action addresses a different case (photon query execution), where an unsupported execution mode limits vectorized engine use. Photon can accelerate supported SQL and DataFrame operators on compatible compute. In the stated problem, the merge scans unrelated historical partitions; this choice would not establish the required predicate-limited merge decision.

Configure supported min/max worker settings for the workload. This implement action addresses a different case (autoscaling right-size), where a fixed high-worker count wastes resources on quiet days. Supported autoscaling can adapt worker count within configured bounds. In the stated problem, the merge scans unrelated historical partitions; this choice would not establish the required predicate-limited merge decision.

Tune executor-side partition sizing or skew rather than only driver memory. This design action addresses a different case (spark ui failure stage), where operators increase driver memory but failures occur on executors. Spark UI task failures and shuffle/spill metrics distinguish worker pressure from driver issues. In the stated problem, deployers have no record of the previous working configuration; this choice would not establish the required rollback deployment decision.

Use branch-based review and merge before deployment. This design action addresses a different case (git folder collaboration), where there is no controlled code review or rollback history. Databricks Git folders connect workspace development to version control. In the stated problem, deployers have no record of the previous working configuration; this choice would not establish the required rollback deployment decision.

Define a controlled change-management path for resource configuration. This design action addresses a different case (unmanaged resource drift), where subsequent CI redeployment unexpectedly overwrites it. Declarative source of truth should include intentional job-resource changes. In the stated problem, deployers have no record of the previous working configuration; this choice would not establish the required rollback deployment decision.

Design a governed cost dashboard grouped by job/workload labels. This design action addresses a different case (billing usage monitoring), where cost reports omit some job and workspace labels. Databricks system billing tables can expose usage records for cost attribution. In the stated problem, scheduled updates are spaced several hours apart; this choice would not establish the required pipeline update cadence decision.

Select right-sized job compute or supported serverless execution for intermittent workloads. This design action addresses a different case (compute utilization), where most provisioned resources sit idle between job runs. Compute metrics and usage history distinguish idle capacity from active work. In the stated problem, scheduled updates are spaced several hours apart; this choice would not establish the required pipeline update cadence decision.

Choose a data-layout or predicate rewrite tied to scan metrics. This design action addresses a different case (query profile scans), where operators assume the query is always CPU-bound. Query Profile identifies scan, pruning and shuffle behavior for SQL workloads. In the stated problem, scheduled updates are spaced several hours apart; this choice would not establish the required pipeline update cadence decision.

Inspect source-to-dashboard lineage for missing quality layers. This diagnose action addresses a different case (medallion bronze silver gold), where malformed source events contaminate metrics without an intermediate quality boundary. Bronze, silver and gold layers separate raw capture, validated refinement and business presentation. In the stated problem, interactive queries scan billions of detail rows for identical totals; this choice would not establish the required aggregate gold model decision.

Inspect membership cardinalities and duplicated fact amounts. This diagnose action addresses a different case (many-to-many bridge), where joining facts directly to the membership table multiplies totals. A bridge table models many-to-many relationships at an explicit membership grain. In the stated problem, interactive queries scan billions of detail rows for identical totals; this choice would not establish the required aggregate gold model decision.

Inspect table grains and dimension join paths used by reports. This diagnose action addresses a different case (star schema analytics), where a denormalized mixed-grain table produces redundant attributes and expensive corrections. A star schema links a clear-grain fact to reusable dimensions for consistent analytics. In the stated problem, interactive queries scan billions of detail rows for identical totals; this choice would not establish the required aggregate gold model decision.

Query facts as of past dates and verify the appropriate historical tier. This validate action addresses a different case (scd type 2 effective dates), where a single current tier overwrites history in the dimension. SCD Type 2 stores effective start/end intervals for distinct historical dimension versions. In the stated problem, a denormalized mixed-grain table produces redundant attributes and expensive corrections; this choice would not establish the required star schema analytics decision.

Reconcile total revenue against the approved source aggregates. This validate action addresses a different case (fact table grain), where summing revenue double-counts orders with multiple items. A dimensional fact must have one clearly documented row grain. In the stated problem, a denormalized mixed-grain table produces redundant attributes and expensive corrections; this choice would not establish the required star schema analytics decision.

Join reports across marts and verify consistent country totals. This validate action addresses a different case (conformed dimensions), where the same country appears under conflicting dimension keys across marts. A conformed dimension provides common attribute definitions across fact models. In the stated problem, a denormalized mixed-grain table produces redundant attributes and expensive corrections; this choice would not establish the required star schema analytics decision.

Inspect current owner and authorized ownership transfer process. This diagnose action addresses a different case (ownership reassignment), where new data stewards cannot maintain its grants. Unity Catalog ownership should be assigned to a maintained principal. In the stated problem, it uses notebook-specific private metadata APIs that break after upgrades; this choice would not establish the required information schema discovery decision.

Inspect notebook defaults and catalog settings for both environments. This diagnose action addresses a different case (environment catalog isolation), where both environments use the same default catalog name in notebooks. Environment-specific catalogs and explicit target names reduce cross-environment writes. In the stated problem, it uses notebook-specific private metadata APIs that break after upgrades; this choice would not establish the required information schema discovery decision.

Inspect effective parent usage and table SELECT grants. This diagnose action addresses a different case (catalog privilege inheritance), where the team lacks USE CATALOG and USE SCHEMA on the parent containers. Unity Catalog object access generally requires relevant parent usage privileges. In the stated problem, it uses notebook-specific private metadata APIs that break after upgrades; this choice would not establish the required information schema discovery decision.

Attach the supported row filter to the eligible table. This implement action addresses a different case (unity catalog row filter), where a shared table currently returns all regions to every reader. Unity Catalog row filters can restrict row visibility through governed policies. In the stated problem, deleting a row from only the gold table leaves copies elsewhere; this choice would not establish the required data subject request decision.

Create the aggregation view and grant SELECT only on the view. This implement action addresses a different case (secure view sharing), where granting SELECT on the raw fact table violates minimization. A governed aggregation view can expose only approved derived information. In the stated problem, deleting a row from only the gold table leaves copies elsewhere; this choice would not establish the required data subject request decision.

Grant only required read privileges on the external location. This implement action addresses a different case (storage credential scope), where engineers propose a credential allowing access to all company buckets. Unity Catalog storage credentials and external locations can constrain storage access. In the stated problem, deleting a row from only the gold table leaves copies elsewhere; this choice would not establish the required data subject request decision.

Replace a scalar Python UDF with supported column expressions or a Pandas UDF. This implement action addresses a different case (vectorized udf), where row-by-row Python invocation dominates stage runtime. Pandas UDFs process batches through Arrow rather than per-row Python calls. In the stated problem, periodic full-refresh queries miss required incremental freshness; this choice would not establish the required streaming table choice decision.

Include the unique tie-breaker in the supported sequence expression. This implement action addresses a different case (cdc duplicate sequence), where the processing order for tied source events is nondeterministic. A deterministic sequencing contract needs a unique ordered event position. In the stated problem, periodic full-refresh queries miss required incremental freshness; this choice would not establish the required streaming table choice decision.

Create the materialized view and configure its supported refresh schedule. This implement action addresses a different case (materialized view choice), where each dashboard query recomputes the same expensive aggregation. A materialized view maintains a precomputed query result through refresh. In the stated problem, periodic full-refresh queries miss required incremental freshness; this choice would not establish the required streaming table choice decision.

Inspect current owner and authorized ownership transfer process. This diagnose action addresses a different case (ownership reassignment), where new data stewards cannot maintain its grants. Unity Catalog ownership should be assigned to a maintained principal. In the stated problem, investigators cannot tell which upstream transformation produced it; this choice would not establish the required lineage tracking decision.

Inspect asset comments and ownership for critical reporting tables. This diagnose action addresses a different case (catalog descriptions), where table and column metadata lack meaningful descriptions. Unity Catalog comments improve discoverability of governed data assets. In the stated problem, investigators cannot tell which upstream transformation produced it; this choice would not establish the required lineage tracking decision.

Inspect catalog and schema managed-location settings. This diagnose action addresses a different case (managed storage ownership), where the data platform cannot apply consistent lifecycle governance. Managed locations centralize storage ownership for Unity Catalog managed assets. In the stated problem, investigators cannot tell which upstream transformation produced it; this choice would not establish the required lineage tracking decision.