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Left outer join retains left-side customers even without matching orders. It would address preserve customers absent from purchase fact, not find orphan sales account references.

Append adds rows from compatible tables without matching them on a key. That targets concatenate time-partitioned transactions, not find orphan sales account references.

Merge joins columns from matching rows across two tables. It may suit enrich fact rows with dimension attributes, not find orphan sales account references.

Aggregated pivoting creates cross-tab columns from long fact data. Its scope is produce summarized region cross-tab, not restore orientation of a rotated table.

Unpivot transforms repeated category columns into attribute-value rows for analytical modeling. That is meant for normalize wide month columns, not restore orientation of a rotated table.

Pivot turns distinct row attribute values into separate columns. It would address create one column per survey question, not restore orientation of a rotated table.

Text combination produces a single presentation field without changing the original keys. It would address create formatted location descriptions, not derive product category prefix.

Key normalization reduces false nonmatches due to controlled formatting differences. It may suit standardize textual join keys, not derive product category prefix.

Delimiter-based splitting exposes distinct components used in filters and joins. It is useful for separate structured identifier components, not for derive product category prefix.

Grouping reduces detailed events to one count per page key. It is useful for count page views by identifier, not for first shipment timestamp per order.

Multiple grouping keys define the aggregation grain and result totals. Its scope is monthly customer revenue summary, not first shipment timestamp per order.

A weighted average accounts for unequal transaction quantities. It would address quantity-weighted unit price, not first shipment timestamp per order.

XML navigation converts nested element structure into a tabular representation. It would address load hierarchical XML purchases, not explode nested order line arrays.

List-to-table and record expansion flatten order objects to rows. That targets tabular JSON order collection, not explode nested order line arrays.

Record expansion extracts child properties while preserving parent row context. It may suit flatten nested address properties, not explode nested order line arrays.

Referenced queries depend on upstream column names and transformation output. Its scope is repair broken referenced query dependencies, not avoid loading intermediate staging tables.

References reuse a base query expression and continue with distinct transformations. That is meant for branch shared cleaned query logic, not avoid loading intermediate staging tables.

Duplicate creates a separate step definition that no longer follows the original's edits. It would address isolate an experimental transformation copy, not avoid loading intermediate staging tables.

A row-wise M expression derives transaction-level amounts before model load. It would address derive gross amount in Power Query, not hours-to-minutes duration conversion.

Calendar-aware transformation maps dates to organization-defined fiscal boundaries. It may suit calculate nonstandard fiscal quarter, not hours-to-minutes duration conversion.

Conditional Column implements a rule-based categorical transform from existing fields. It is useful for classifying delays using a column rule, not for hours-to-minutes duration conversion.

Header promotion converts label values into column names. It is useful for promote actual field names, not for standardize expanded column captions.

Removing metadata lines aligns the true header row to the first position. Its scope is skip decorative rows before header promotion, not standardize expanded column captions.

Fixed projection lists can hide newly introduced source attributes. It would address handle evolving source schema intentionally, not standardize expanded column captions.

Conformed dimensions support consistent cross-fact slicing while retaining different fact grains. It would address multiple fact tables sharing product dimension, not monthly target snapshot model.

Facts capture measurable events at a defined grain and reference dimensions. That targets preserve order-line fact grain, not monthly target snapshot model.

Dimensions provide descriptive attributes and the one-side keys for fact filtering. It may suit descriptive product dimension, not monthly target snapshot model.

Unique complete date keys support date relationships and time intelligence. Its scope is complete calendar dimension key, not stable product model relationship key.

Slowly changing dimension versions require distinct keys to retain time-valid attributes. That is meant for history-safe customer dimension key, not stable product model relationship key.

Both columns determine the fact grain; dropping one creates collisions. It would address unique purchase-line identifier, not stable product model relationship key.

Loading makes the dimension available in the semantic model for relationships and reports. It would address materialize a lookup dimension, not remove unnecessary sensitive source columns.

Subtotal records duplicate values already represented by detail rows. It may suit avoid source subtotal double counting, not remove unnecessary sensitive source columns.

Disable Load prevents redundant model storage while preserving downstream query logic. It is useful for staging-only transformation query, not for removing unnecessary sensitive source columns.