CDW110
AttributeDim - ANS-Stores the listing of all attributes used by the AttributeValueDim machine
AttributeValueDims - ANS-One shape of EAV facts in Caboodle. Contain characteristic-fee
pairs
Bridge table - ANS-This is required to map a many-to-many relationship such as sufferers
and their diagnoses
Bridge tables - ANS-For many to many relationships
Caboodle reporting database - ANS-Comes from the staging database and is used by
caboodle record writers to write down reports
Caboodle staging database - ANS-Data is transformed, checked for referential integrity, and
wiped clean
Change monitoring - ANS-A belongings of a table that informs us how Caboodle might be up
to date when adjustments are made to the source databases
Change tracking kinds - ANS-1) None, 2) Snapshot Change Tracking
Compared to Fact tables, Dimension tables generally comprise.. - ANS-More records and
less lookup columns
Data dictionary column segment - ANS-Name, statistics type, availability in SlicerDicer, links
to (research columns), chronicles info, description
Data dictionary dependencies phase - ANS-Indicates what database gadgets a desk is
dependent on. Clarity or caboodle tables and columns
Data dictionary ER diagram phase - ANS-Classic megastar schema for investigating joins.
Only for Fact and DataMart. Non be a part of columns can also be indexed via clicking the
important thing to increase into complete column list
Data dictionary lineage section - ANS-Available in multiplied column. Contains chronicles INI
nd item numbers and the way the item can be used in SlicerDicer classes (FDS statistics)
Data dictionary assessment segment - ANS-Description, type of database item, granularity
Data dictionary queries segment - ANS-Lists SSIS packages that populate the table and
their queries
, Data mart - ANS-Brings collectively points from numerous DMCs into one location, serving
as a complete statistics source for a selected reporting need.
DataMart - ANS-Report on information points from several DMCs in a single place
dbo schema - ANS-Stores reporting facts and acts as the data supply for SlicerDicer
Dimension tables - ANS-One row for each entity inside the set. Examples are ProviderDim,
PatientDim
DMC - ANS-Data Model Component. Consists of the table, the programs used to populate
the table, and underlying metadata tables that assist with ETL
EAV model - ANS-Entity attribute price. For cases wherein attributes exchange often.
Fact tables - ANS-One row for every incidence of a few large, measurable event. Examples
are MedicationOrderFact and EncounterFact
FilteredAccess Schema - ANS-Similar to FullAccess, but consequences are filtered based
totally on user security
FullAccess Schema - ANS-Everything for report writers from the dbo schema and greater
How are you able to inform a column is lookup? - ANS-Ends in -Key
How to filter deleted records from a Fact table? - ANS-Use the Count column. It shops a 1
while the row must be blanketed in a calculation and a 0 when no longer
How to pick out inferred rows in a desk? - ANS-_IsInferred column
How to look what schema is being used for reports? - ANS-SELECT SCHEMA_NAME()
How to tell if a table is using photo trade monitoring? - ANS-Chip within the overview
segment of the table
Inferred row - ANS-Placeholder rows that are delivered to the destination desk whilst the
lookup column price does no longer have a healthy within the vacation spot desk
Lookup column - ANS-A column in a single table whose cost identifies at least one row in
some other desk. Most tables in Caboodle have as a minimum one
Non Snapchat table granularity - ANS-One row consistent with entity extracted to the desk
Non image table - ANS-Reflect the present day content material of the supply data at the
time of the most current extract
Referential Integrity - ANS-Lookup columns will always have a value and that value will find
a in shape in the destination table
AttributeDim - ANS-Stores the listing of all attributes used by the AttributeValueDim machine
AttributeValueDims - ANS-One shape of EAV facts in Caboodle. Contain characteristic-fee
pairs
Bridge table - ANS-This is required to map a many-to-many relationship such as sufferers
and their diagnoses
Bridge tables - ANS-For many to many relationships
Caboodle reporting database - ANS-Comes from the staging database and is used by
caboodle record writers to write down reports
Caboodle staging database - ANS-Data is transformed, checked for referential integrity, and
wiped clean
Change monitoring - ANS-A belongings of a table that informs us how Caboodle might be up
to date when adjustments are made to the source databases
Change tracking kinds - ANS-1) None, 2) Snapshot Change Tracking
Compared to Fact tables, Dimension tables generally comprise.. - ANS-More records and
less lookup columns
Data dictionary column segment - ANS-Name, statistics type, availability in SlicerDicer, links
to (research columns), chronicles info, description
Data dictionary dependencies phase - ANS-Indicates what database gadgets a desk is
dependent on. Clarity or caboodle tables and columns
Data dictionary ER diagram phase - ANS-Classic megastar schema for investigating joins.
Only for Fact and DataMart. Non be a part of columns can also be indexed via clicking the
important thing to increase into complete column list
Data dictionary lineage section - ANS-Available in multiplied column. Contains chronicles INI
nd item numbers and the way the item can be used in SlicerDicer classes (FDS statistics)
Data dictionary assessment segment - ANS-Description, type of database item, granularity
Data dictionary queries segment - ANS-Lists SSIS packages that populate the table and
their queries
, Data mart - ANS-Brings collectively points from numerous DMCs into one location, serving
as a complete statistics source for a selected reporting need.
DataMart - ANS-Report on information points from several DMCs in a single place
dbo schema - ANS-Stores reporting facts and acts as the data supply for SlicerDicer
Dimension tables - ANS-One row for each entity inside the set. Examples are ProviderDim,
PatientDim
DMC - ANS-Data Model Component. Consists of the table, the programs used to populate
the table, and underlying metadata tables that assist with ETL
EAV model - ANS-Entity attribute price. For cases wherein attributes exchange often.
Fact tables - ANS-One row for every incidence of a few large, measurable event. Examples
are MedicationOrderFact and EncounterFact
FilteredAccess Schema - ANS-Similar to FullAccess, but consequences are filtered based
totally on user security
FullAccess Schema - ANS-Everything for report writers from the dbo schema and greater
How are you able to inform a column is lookup? - ANS-Ends in -Key
How to filter deleted records from a Fact table? - ANS-Use the Count column. It shops a 1
while the row must be blanketed in a calculation and a 0 when no longer
How to pick out inferred rows in a desk? - ANS-_IsInferred column
How to look what schema is being used for reports? - ANS-SELECT SCHEMA_NAME()
How to tell if a table is using photo trade monitoring? - ANS-Chip within the overview
segment of the table
Inferred row - ANS-Placeholder rows that are delivered to the destination desk whilst the
lookup column price does no longer have a healthy within the vacation spot desk
Lookup column - ANS-A column in a single table whose cost identifies at least one row in
some other desk. Most tables in Caboodle have as a minimum one
Non Snapchat table granularity - ANS-One row consistent with entity extracted to the desk
Non image table - ANS-Reflect the present day content material of the supply data at the
time of the most current extract
Referential Integrity - ANS-Lookup columns will always have a value and that value will find
a in shape in the destination table
