PurposeFacets of the DQAFOrganization of the ChapterMeasurement Type #1: Dataset Completeness—Sufficiency of Metadata and Reference DataMeasurement Type #2: Consistent Formatting in One FieldMeasurement Type #3: Consistent Formatting, Cross-tableMeasurement Type #4: Consistent Use of Default Value in One FieldMeasurement Type #5: Consistent Use of Default Values, Cross-tableMeasurement Type #6: Timely Delivery of Data for ProcessingMeasurement Type #7: Dataset Completeness—Availability for ProcessingMeasurement Type #8: Dataset Completeness—Record Counts to Control RecordsMeasurement Type #9: Dataset Completeness—Summarized Amount Field DataMeasurement Type #10: Dataset Completeness—Size Compared to Past SizesMeasurement Type #11: Record Completeness—LengthMeasurement Type #12: Field Completeness—Non-Nullable FieldsMeasurement Type #13: Dataset Integrity—De-DuplicationMeasurement Type #14: Dataset Integrity—Duplicate Record Reasonability CheckMeasurement Type #15: Field Content Completeness—Defaults from SourceMeasurement Type #16: Dataset Completeness Based on Date CriteriaMeasurement Type #17: Dataset Reasonability Based on Date CriteriaMeasurement Type #18: Field Content Completeness—Received Data is Missing Fields Critical to ProcessingMeasurement Type #19: Dataset Completeness—Balance Record Counts Through a ProcessMeasurement Type #20: Dataset Completeness—Reasons for Rejecting RecordsMeasurement Type #21: Dataset Completeness Through a Process—Ratio of Input to OutputMeasurement Type #22: Dataset Completeness Through a Process—Balance Amount FieldsMeasurement Type #23: Field Content Completeness—Ratio of Summed Amount FieldsMeasurement Type #24: Field Content Completeness—Defaults from DerivationMeasurement Type #25: Data Processing DurationMeasurement Type #26: Timely Availability of Data for AccessMeasurement Type #27: Validity Check, Single Field, Detailed ResultsMeasurement Type #28: Validity Check, Roll-upMeasurement Logical Data ModelMeasurement Type #29: Validity Check, Multiple Columns within a Table, Detailed ResultsMeasurement Type #30: Consistent Column ProfileMeasurement Type #31: Consistent Dataset Content, Distinct Count of Represented Entity, with Ratios to Record CountsMeasurement Type #32 Consistent Dataset Content, Ratio of Distinct Counts of Two Represented EntitiesMeasurement Type #33: Consistent Multicolumn ProfileMeasurement Type #34: Chronology Consistent with Business Rules within a TableMeasurement Type #35: Consistent Time Elapsed (hours, days, months, etc.)Measurement Type #36: Consistent Amount Field Calculations Across Secondary FieldsMeasurement Type #37: Consistent Record Counts by Aggregated DateMeasurement Type #38: Consistent Amount Field Data by Aggregated DateMeasurement Type #39: Parent/Child Referential IntegrityMeasurement Type #40: Child/Parent Referential IntegrityMeasurement Type #41: Validity Check, Cross Table, Detailed ResultsMeasurement Type #42: Consistent Cross-table Multicolumn ProfileMeasurement Type #43: Chronology Consistent with Business Rules Across-tablesMeasurement Type #44: Consistent Cross-table Amount Column CalculationsMeasurement Type #45: Consistent Cross-Table Amount Columns by Aggregated DatesMeasurement Type #46: Consistency Compared to External BenchmarksMeasurement Type #47: Dataset Completeness—Overall Sufficiency for Defined PurposesMeasurement Type #48: Dataset Completeness—Overall Sufficiency of Measures and ControlsConcluding Thoughts: Know Your Data