Note: The results listed above reflect the default match sensitivity (85).
SAS Quality Knowledge Base for Contact Information 26
In the Quality Knowledge Base, the English definitions are shared by all English-language locales. Shared English definitions are described below.
Case Definitions
Extraction Definitions
Gender Analysis Definitions
Identification Analysis Definitions
Match Definitions
Parse Definitions
Pattern Analysis Definitions
Standardization Definitions
Inherited Definitions
| Proper (Address) | ||
|---|---|---|
| Description | The Proper (Address) case definition propercases addresses. | |
| Input | Output | |
| Examples | 11TH FLOOR | 11th Floor |
| po box 125 | PO Box 125 | |
| Remarks | ||
| Proper (Business Title) | ||
|---|---|---|
| Description | The Proper (Business Title) case definition propercases business titles. | |
| Input | Output | |
| Examples | ceo | CEO |
| SALES MANAGER | Sales Manager | |
| Remarks | ||
| Proper (Given Name) | ||
|---|---|---|
| Description |
The Proper (Given Name) case definition propercases given names of individuals. |
|
| Examples | Input | Output |
| aj | AJ | |
| mckensie | McKensie | |
| anne-marie | Anne-Marie | |
| Remarks | ||
| Proper (Name) | ||
|---|---|---|
| Description | The Proper (Name) case definition propercases names of individuals. | |
| Examples | Input | Output |
| GWENDOL GUTTERMOTH | Gwendol Guttermoth | |
| JOHN O'ROURKE | John O'Rourke | |
| ronald chung-hui mcdonald | Ronald Chung-Hui McDonald | |
| Remarks | ||
| Proper (Organization) | ||
|---|---|---|
| Description | The Proper (Organization) case definition propercases organization names. | |
| Examples | Input | Output |
| DATAFLUX CORPORATION | DataFlux Corporation | |
| sas institute | SAS Institute | |
| Remarks | ||
| Proper (Site) | ||
|---|---|---|
| Description | The Proper (Site) case definition propercases organization sites. | |
| Examples | Input | Output |
| of new zealand | of New Zealand | |
| uk | UK | |
| Remarks | ||
| Upper (Legal Form) | ||
|---|---|---|
| Description | The Upper (Legal Form) case definition uppercases organization legal forms. | |
| Examples | Input | Output |
| inc | Inc | |
| LTD | Ltd | |
| sp zoo | SP ZOO | |
| Remarks | Legal forms default to uppercasing. Some known forms are propercased. | |
None.
| Name | ||
|---|---|---|
| Description | The Name gender analysis definition determines the gender of a name. | |
| Possible Outputs | M F U |
|
| Examples | Input | Output |
| Sandi Baker | F | |
| Pat Young, Jr. | M | |
| T. Millhouse | U | |
| Remarks | ||
| Contact Info | ||
|---|---|---|
| Description | The Contact Info identification analysis definition identifies the contact information that is represented by a string. | |
| Possible Outputs | NAME ORGANIZATION NAME/ORGANIZATION UNKNOWN BLANK |
|
| Examples | Input | Output |
| DataFlux Corporation | ORGANIZATION | |
| Tony Fisher | NAME | |
| Joe Smith DBA Some Company Name | NAME/ORGANIZATION | |
| john.smith@sas.com | ||
| BLANK | ||
| Fisher | UNKNOWN | |
| Remarks | ||
| Field Name | ||
|---|---|---|
| Description |
The Field Name identification analysis definition identifies database column names. |
|
| Possible Outputs | NAME ORGANIZATION ADDRESS CITY STATE/PROVINCE POSTALCODE COUNTRY PHONE DATE UNKNOWN URL GENDER MATCHCODE PERSONAL_ID ORGANIZATION_ID GENERIC_ID COUNTY MARITAL_STATUS |
|
| Examples | Input | Output |
| Company Name | ORGANIZATION | |
| Address | ADDRESS | |
| Telephone | PHONE | |
| Remarks |
This definition is recommended to determine the type of data stored in a database column based on the name of the column. |
|
| Offensive | ||
|---|---|---|
| Description | The Offensive identification analysis definition identifies potentially offensive words and phrases. | |
| Possible Outputs | OFF_ENUSA_1 OFF_ENUSA_2 OFF_ENGBR_1 OFF_ENGBR_2 OFF_FRFRA_1 OFF_FRFRA_2 INVALID, PASS |
|
| Examples | Input | Output |
| ababab | INVALID | |
| none of your business | INVALID | |
| Mr. Dork | OFF_ENUSA_1 | |
| Remarks | Values in some of the libraries associated with this definition would be considered offensive by most. SAS in no way condones or approves of the use of this information for any reason other than that for which it was designed. | |
| Business Title | ||
|---|---|---|
| Description | The Business Title match definition generates match codes which can be used to cluster records containing business title information. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| CEO | 0 | |
| Chief Executive Officer | 0 | |
| Remarks |
|
|
| Country | ||
|---|---|---|
| Description | The Country match definition generates match codes which can be used to cluster records containing country names. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| United States | 0 | |
| Great Britain | 1 | |
| Remarks |
|
|
| Date (DMY) | ||
|---|---|---|
| Description | The Date (DMY) match definition generates match codes which can be used to cluster records containing dates that have the format DMY. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| 05March1969 | 1 | |
| 5-3-1969 | 1 | |
| Remarks |
|
|
| Date (DMY) (with Combinations) | ||
|---|---|---|
| Description | The Date (DMY) (with Combinations) match definition generates match codes which can be used to cluster records containing dates, with a score for each match code, that have the format DMY. | |
| Max Length of Match Code | 15 characters | |
| Example 1 | Input | Cluster ID |
| Sensitivities 50 - 100 Weight 100 |
01/02/2013 | 0 |
| Feb-01-2013 | 0 | |
| Example 2 | Input | Cluster ID |
| Sensitivities 50 - 100 Weight 40 |
Feb-01-2013 | 1 |
| 01/02/2013 | 1 | |
| 02/01/2013 | 1 | |
| Remarks |
A date with DMY format will match with the date with MDY format. This definition generates one or more match codes for each input string. The number of match codes generated for an input string depends on the content of the string. Each match code represents a combination of different parts of the input string; this enables two strings to be matched even when some parts of one or both of the strings differ. See the examples above for an illustration of clusters that can be produced using match codes generated by this definition. Note that a consequence of generating multiple match codes is that a record can be placed in more than one cluster by a subsequent clustering operation. Therefore, special attention should be given to the entity resolution process when using this definition. Generation of multiple match codes is achieved through the use of token-combination rules in the match definition. Each match code generated by the definition is associated with one token-combination rule. There is a weight assigned to each rule; each rule's weight is used to calculate a score that is assigned to the match code that is generated by that rule. The score for a match code is equal to the weight of the rule used to generate the match code times the sensitivity that is selected when the definition is executed. When a record is clustered, the score for the record’s match code represents the confidence with which we can assert that the record belongs in the cluster. Note that when different rules lead to identical clustering results, the scores of the match codes generated by the different rules can be aggregated using the Cluster Aggregation node in a Data Job. The Cluster Aggregation node allows several different methods for aggregating match code scores, such as minimum, maximum, or mean across instances of a record, or minimum, maximum, or mean across all records in a cluster. For information on the Cluster Aggregation node, refer to the documentation provided with the DataFlux Data Management Studio installation. |
|
| Date (MDY) | ||
|---|---|---|
| Description | The Date (MDY) match definition generates match codes which can be used to cluster records containing dates that have the format MDY. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| 8.30.1997 | 0 | |
| August 30th, 1997 | 0 | |
| Remarks |
|
|
| Date (MDY) (with Combinations) | ||
|---|---|---|
| Description | The Date (MDY) (with Combinations) match definition generates match codes which can be used to cluster records containing dates, with a score for each match code, that have the format MDY. | |
| Max Length of Match Code | 15 characters | |
| Example 1 | Input | Cluster ID |
| Sensitivities 50 - 100 Weight 100 |
01/02/2013 | 0 |
| Jan-02-2013 | 0 | |
| Example 2 | Input | Cluster ID |
| Sensitivities 50 - 100 Weight 40 |
Jan-02-2013 | 1 |
| 02/01/2013 | 1 | |
| Remarks |
A date with MDY format will match with the date with DMY format. This definition generates one or more match codes for each input string. The number of match codes generated for an input string depends on the content of the string. Each match code represents a combination of different parts of the input string; this enables two strings to be matched even when some parts of one or both of the strings differ. See the examples above for an illustration of clusters that may be produced using match codes generated by this definition. Note that a consequence of generating multiple match codes is that a record can be placed in more than one cluster by a subsequent clustering operation. Therefore, special attention should be given to the entity resolution process when using this definition. Generation of multiple match codes is achieved through the use of token-combination rules in the match definition. Each match code generated by the definition is associated with one token-combination rule. There is a weight assigned to each rule; each rule's weight is used to calculate a score that is assigned to the match code that is generated by that rule. The score for a match code is equal to the weight of the rule used to generate the match code times the sensitivity that is selected when the definition is executed. When a record is clustered, the score for the record’s match code represents the confidence with which we can assert that the record belongs in the cluster. Note that when different rules lead to identical clustering results, the scores of the match codes generated by the different rules can be aggregated using the Cluster Aggregation node in a Data Job. The Cluster Aggregation node allows several different methods for aggregating match code scores, such as minimum, maximum, or mean across instances of a record, or minimum, maximum, or mean across all records in a cluster. For information on the Cluster Aggregation node, refer to the documentation provided with the DataFlux Data Management Studio installation. |
|
| Date (YMD) | ||
|---|---|---|
| Description | The Date/Time (YMD) match definition generates match codes which can be used to cluster records containing date/time information. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| 2002dec31 | 1 | |
| 2002.12.31 | 1 | |
| Remarks |
|
|
| Date/Time (DMY) | ||
|---|---|---|
| Description | The Date/Time (DMY) match definition generates match codes which can be used to cluster records containing date/time information. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| 20 Jul 2969 02:20:32 | 0 | |
| 20/7/69 02:20:32 | 0 | |
| Remarks |
|
|
| Date/Time (MDY) | ||
|---|---|---|
| Description | The Date/Time (MDY) match definition generates match codes which can be used to cluster records containing date/time information. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| Nov-06-2001 2:32 PM | 1 | |
| 11/6/01 2:32 PM | 1 | |
| Remarks |
|
|
| Date/Time (YMD) | ||
|---|---|---|
| Description | The Date/Time (YMD) match definition generates match codes which can be used to cluster records containing date/time information. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| 1999.10.11 22:40:00+04:00 | 0 | |
| 99/10/11 22:40:00+04:00 | 0 | |
| Remarks |
|
|
| Field Name | ||
|---|---|---|
| Description | The Field Name match definition generates match codes which can be used to cluster records containing database field names. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| Company Name | 0 | |
| Organization | 0 | |
| Home_Address | 1 | |
| Address | 1 | |
| Telephone | 2 | |
| PHONE | 2 | |
| First_Name | 3 | |
| NAME | 3 | |
| Remarks |
This definition should be used to find potential matches between database column names.
|
|
| Name | ||
|---|---|---|
| Description | The Name match definition generates match codes which can be used to cluster records containing names of individuals. | |
| Max Length of Match Code | 27 characters | |
| Examples | Input | Cluster ID |
| Mary Shafer | 0 | |
| Mrs. Marian V. Schaeffer | 0 | |
| Shaffer, Mary | 0 | |
| Remarks |
|
|
| Name (with Combinations) | ||
|---|---|---|
| Description | The Name (with Combinations) match definition generates match codes which can be used to cluster records containing names of individuals. | |
| Max Length of Match Code | 27 characters | |
| Example 1 | Input | Cluster ID |
| Sensitivities 50 - 100 Weight 100 |
Mary Shafer | 0 |
| Shaffer, Mary | 0 | |
| Example 2 | Input | Cluster ID |
| Sensitivities 50 - 100 Weight 20 |
D Harrison Wood | 1 |
| Harrison Wood | 1 | |
| Example 2 | Input | Cluster ID |
| Sensitivities 50 - 100 Weight 80 |
Martha Newell-Warner | 2 |
| Martha Newell | 2 | |
| Example 3 | Input | Cluster ID |
| Sensitivities 50 - 100 Weight 50 |
John Elton | 3 |
| Elton John | 3 | |
| Remarks |
This definition generates one or more match codes for each input string. The number of match codes generated for an input string depends on the content of the string. Each match code represents a combination of different parts of the input string; this enables two strings to be matched even when some parts of one or both of the strings differ. See the examples above for an illustration of clusters that might be produced using match codes generated by this definition. Note that a consequence of generating multiple match codes is that a record might be placed in more than one cluster by a subsequent clustering operation. Therefore, special attention should be given to the entity resolution process when using this definition. Generation of multiple match codes is achieved through the use of token-combination rules in the match definition. Each match code generated by the definition is associated with one token-combination rule. There is a weight assigned to each rule; each rule's weight is used to calculate a score that is assigned to the match code that is generated by that rule. The score for a match code is equal to the weight of the rule used to generate the match code times the sensitivity that is selected when the definition is executed. When a record is clustered, the score for the record’s match code represents the confidence with which we can assert that the record belongs in the cluster. Note that when different rules lead to identical clustering results, the scores of the match codes generated by the different rules might be aggregated using the Cluster Aggregation node in a Data Job. The Cluster Aggregation node allows several different methods for aggregating match code scores, such as minimum, maximum, or mean across instances of a record, or minimum, maximum, or mean across all records in a cluster. For information on the Cluster Aggregation node, refer to the documentation provided with the DataFlux Data Management Studio installation. |
|
| Organization | ||
|---|---|---|
| Description | The Organization match definition generates match codes which can be used to cluster records containing organization names. | |
| Max Length of Match Code | 35 characters | |
| Examples | Input | Cluster ID |
| DataFlux Corporation | 0 | |
| DataFlex LLC | 0 | |
| SAS Institute | 0 | |
| SAS Institute, Canada | 0 | |
| Remarks |
|
|
| Text | ||
|---|---|---|
| Description | The Text match definition generates match codes which can be used to cluster records containing general text strings. | |
| Max Length of Match Code | 15 characters | |
| Examples | Input | Cluster ID |
| they went | 0 | |
| you are | 1 | |
| you're | 1 | |
| Remarks |
|
|
| Business Title | |||
|---|---|---|---|
| Description |
The Business Title parse definition parses business title information into a set of tokens. |
||
| Output Tokens | Position Level Location Department Grade |
||
| Example | Input | Output Token | Output |
| Marketing Director | Position | Director | |
| Level | |||
| Location | |||
| Department | Marketing | ||
| Grade | |||
| Remarks | |||
| Date (DMY) | |||
|---|---|---|---|
| Description |
The Date (DMY) parse definition parses dates with format DMY into a set of tokens. |
||
| Output Tokens | Day Month Year |
||
| Example | Input | Output Token | Output |
| 05March1969 | Day | 05 | |
| Month | March | ||
| Year | 1969 | ||
| Remarks | |||
| Date (MDY) | |||
|---|---|---|---|
| Description | The Date (MDY) parse definition parses dates with format MDY into a set of tokens. | ||
| Output Tokens | Day Month Year |
||
| Example | Input | Output Token | Output |
| 03-05-1969 | Day | 05 | |
| Month | 03 | ||
| Year | 1969 | ||
| Remarks | |||
| Date (YMD) | |||
|---|---|---|---|
| Description | The Date (YMD) parse definition parses dates with format YMD into a set of tokens. | ||
| Output Tokens | Day Month Year |
||
| Example | Input | Output Token | Output |
| 1969.3.5 | Day | 5 | |
| Month | 3 | ||
| Year | 1969 | ||
| Remarks | |||
| Date/Time (DMY) | |||
|---|---|---|---|
| Description | The Date/Time (DMY) parse definition parses dates with format DMY HH:MM:SS into a set of tokens. | ||
| Output Tokens | Year Month Day Weekday Hours Minutes Seconds Time Extension |
||
| Example | Input | Output Token | Output |
| 20 Jul 1969 02:20:32 | Year | 1969 | |
| Month | Jul | ||
| Day | 20 | ||
| Weekday | |||
| Hours | 02 | ||
| Minutes | 20 | ||
| Seconds | 32 | ||
| Time Extension | |||
| Remarks | |||
| Date/Time (MDY) | |||
|---|---|---|---|
| Description | The Date/Time (MDY) parse definition parses dates with format MDY HH:MM:SS into a set of tokens. | ||
| Output Tokens | Year Month Day Weekday Hours Minutes Seconds Time Extension |
||
| Example | Input | Output Token | Output |
| Nov-06-2001 2:32 PM | Year | 2001 | |
| Month | Nov | ||
| Day | 06 | ||
| Weekday | |||
| Hours | 2 | ||
| Minutes | 32 | ||
| Seconds | |||
| Time Extension | PM | ||
| Remarks | |||
| Date/Time (YMD) | |||
|---|---|---|---|
| Description |
The Date/Time (YMD) parse definition parses dates with format YMD HH:MM:SS into a set of tokens. |
||
| Output Tokens | Year Month Day Weekday Hours Minutes Seconds Time Extension |
||
| Example | Input | Output Token | Output |
| 1999.10.11 22:40:00+04:00 | Year | 1999 | |
| Month | 10 | ||
| Day | 11 | ||
| Weekday | |||
| Hours | 22 | ||
| Minutes | 40 | ||
| Seconds | 00 | ||
| Time Extension | +04:00 | ||
| Remarks | |||
| Name | |||
|---|---|---|---|
| Description |
The Name parse definition parses names of individuals into a set of tokens. |
||
| Output Tokens | Prefix Given Name Middle Name Family Name Suffix Title/Additional Info |
||
| Example 1 | Input | Output Token | Output |
| Dr. James Goodnight, CEO | Prefix | Dr. | |
| Given Name | James | ||
| Middle Name | |||
| Family Name | Goodnight | ||
| Suffix | |||
| Title/Additional Info | CEO | ||
| Example 2 | Input | Output Token | Output |
| Smith, Sr., Ronald G. | Prefix | ||
| Given Name | Ronald | ||
| Middle Name | G. | ||
| Family Name | Smith | ||
| Suffix | Sr. | ||
| Title/Additional Info | |||
| Remarks | |||
| Name (Global) | |||
|---|---|---|---|
| Description | The Name (Global) parse definition parses names of individuals into a globally recognized set of tokens. | ||
| Output Tokens | Prefix Given Name Middle Name Family Name Suffix Title/Additional Info |
||
| Example 1 | Input | Output Token | Output |
| Dr. James Goodnight, CEO | Prefix | Dr. | |
| Given Name | James | ||
| Middle Name | |||
| Family Name | Goodnight | ||
| Suffix | |||
| Title/Additional Info | CEO | ||
| Example 2 | Input | Output Token | Output |
| Smith, Sr., Ronald G. | Prefix | ||
| Given Name | Ronald | ||
| Middle Name | G. | ||
| Family Name | Smith | ||
| Suffix | Sr. | ||
| Title/Additional Info | |||
| Remarks | Parse definitions named with the Global keyword use a set of output tokens that is consistent across every locale. Results obtained from these definitions can be stored in the same database fields as the results obtained from definitions of the same name in other locales. | ||
| Name (Multiple Name) | |||
|---|---|---|---|
| Description | The Name (Multiple Name) parse definition parses strings that contain the names of two individuals into a set of tokens. | ||
| Output Tokens | Name 1 Name 2 |
||
| Example 1 | Input | Output Token | Output |
| Mr Jon and Mrs Sally Smith | Name 1 | Mr Jon Smith | |
| Name 2 | Mrs Sally Smith | ||
| Example 2 | Input | Output Token | Output |
| Jon Smith & Pat Young Jr. | Name 1 | Jon Smith | |
| Name 2 | Pat Young Jr. | ||
| Remarks | If only one name is present in the input, the first token is used. | ||
| Organization | |||
|---|---|---|---|
| Description | The Organization parse definition parses organization names into a set of tokens. | ||
| Output Tokens | Name
Legal Form Site Additional Info |
||
| Example 1 | Input | Output Token | Output |
| 3Com Europe Limited | Name | 3Com Europe | |
| Legal Form | Limited | ||
| Site | |||
| Additional Info | |||
| Example 2 | Input | Output Token | Output |
| Corporate Psychology International (CPI) | Name | Corporate Psychology International | |
| Legal Form | |||
| Site | |||
| Additional Info | (CPI) | ||
| Remarks | |||
| Organization (Global) | |||
|---|---|---|---|
| Description | The Organization (Global) parse definition parses organization names into a set of tokens. | ||
| Output Tokens | Name
Legal Form Site Additional Info |
||
| Example 1 | Input | Output Token | Output |
| 3Com Europe Limited | Name | 3Com Europe | |
| Legal Form | Limited | ||
| Site | |||
| Additional Info | |||
| Example 2 | Input | Output Token | Output |
| Corporate Psychology International (CPI) | Name | Corporate Psychology International | |
| Legal Form | |||
| Site | |||
| Additional Info | (CPI) | ||
| Remarks | Parse definitions named with the Global keyword use a set of output tokens that is consistent across every locale. Results obtained from these definitions can be stored in the same database fields as the results obtained from definitions of the same name in other locales. | ||
| Organization (Multiple) | |||
|---|---|---|---|
| Description | The Organization (Multiple) parse definition parses strings that contain the names of one or two organizations into a set of tokens. | ||
| Output Tokens | Organization 1 Organization 2 |
||
| Examples | Input | Output Token | Output |
| THE GINGER CAT T/A EMBROIDERY PLACE LLC | Organization 1 | THE GINGER CAT | |
| Organization 2 | EMBROIDERY PLACE LLC | ||
| Remarks | |||
None.
| Business Title | ||
|---|---|---|
| Description | The Business Title standardization definition standardizes business titles using a parse definition as an initial step. | |
| Examples | Input | Output |
| cfo | CFO | |
| Chief Financial Officer | CFO | |
| sales director | Director, Sales | |
| Remarks | ||
| Business Title (No Parse) | ||
|---|---|---|
| Description | The Business Title (No Parse) standardization definition standardizes business titles without using a parse definition as an initial step. | |
| Examples | Input | Output |
| bus mngr | Business Manager | |
| BUSINESS MGR | Business Manager | |
| sales director | Sales Director | |
| Remarks | ||
| Country | ||
|---|---|---|
| Description |
The Country standardization definition standardizes country names to a common short format. |
|
| Examples | Input | Output |
| UK | UNITED KINGDOM | |
| gbr | UNITED KINGDOM | |
| Remarks | ||
| Country (FIPS) | ||
|---|---|---|
| Description |
The Country (FIPS) standardization definition standardizes country names to the US FIPS code format. |
|
| Examples | Input | Output |
| Czech Republic | EZ | |
| gbr | UK | |
| Remarks | ||
| Country (Internet) | ||
|---|---|---|
| Description |
The Country (Internet) standardization definition standardizes country names to the top-level domain designation. |
|
| Examples | Input | Output |
| Czech Republic | CZ | |
| gbr | UK | |
| Remarks | ||
| Country (ISO 2 Char) | ||
|---|---|---|
| Description | The Country (ISO 2 Char) standardization definition standardizes country names into the ISO-3166 two-character designation. | |
| Examples | Input | Output |
| Czech Republic | CZ | |
| gbr | GB | |
| Remarks | ||
| Country (ISO 3 Char) | ||
|---|---|---|
| Description | The Country (ISO 3 Char) standardization definition standardizes country names into the ISO-3166 three-character designation. | |
| Examples | Input | Output |
| Czech Republic | CZE | |
| gbr | GBR | |
| Remarks | ||
| Country (ISO Number) | ||
|---|---|---|
| Description |
The Country (ISO Number) standardization definition standardizes country names to the ISO-3166 numeric designation. |
|
| Examples | Input | Output |
| Czech Republic | 203 | |
| gbr | 826 | |
| Remarks | ||
| Country (Region) | ||
|---|---|---|
| Description |
The Country (Region) standardization definition standardizes country names to the United Nations region designation. |
|
| Examples | Input | Output |
| Czech Republic | EUROPE | |
| gbr | EUROPE | |
| Remarks | ||
| Country (Sub-Region) | ||
|---|---|---|
| Description |
The Country (Sub-Region) standardization definition standardizes country names to the United Nations sub-region designation. |
|
| Examples | Input | Output |
| Czech Republic | EASTERN EUROPE | |
| gbr | NORTHERN EUROPE | |
| Remarks | ||
| Date (DMY) | ||
|---|---|---|
| Description | The Date (DMY) standardization definition standardizes dates that have format DMY. The output is a zero-padded two-digit day, followed by a zero-padded two-digit month, followed by a four-digit year. The day, month, and year are separated by spaces. | |
| Examples | Input | Output |
| 04/07/02 | 04 07 2002 | |
| 04July05 | 04 07 2005 | |
| 04.07.05 | 04 07 2005 | |
| 04July2005 | 04 07 2005 | |
| 04-07-2005 | 04 07 2005 | |
| Remarks | If the input year is a two-digit value, it is assumed to be within the hundred year span with 2019 as the end of the span. For example, a year of 19 will be 2019, but a year of 20 will be 1920. | |
| Date (MDY) | ||
|---|---|---|
| Description | The Date (MDY) standardization definition standardizes dates that have format MDY. The output is a zero-padded two-digit month, followed by a zero-padded two-digit day, followed by a four-digit year. The month, day, and year are separated by spaces. | |
| Examples | Input | Output |
| July04, 02 | 07 04 2002 | |
| 07/04/02 | 07 04 2002 | |
| July04, 05 | 07 04 2005 | |
| 07.04.05 | 07 04 2005 | |
| July 4, 2005 | 07 04 2005 | |
| 07-04-2005 | 07 04 2005 | |
| Remarks | If the input year is a two-digit value, it is assumed to be within the hundred year span with 2019 as the end of the span. For example, a year of 19 will be 2019, but a year of 20 will be 1920. | |
| Date (YMD) | ||
|---|---|---|
| Description | The Date (YMD) standardization definition standardizes dates that have format YMD. The output is a four-digit year, followed by a zero-padded two-digit month, followed by a zero-padded two-digit day. The year, month, and day are separated by spaces. | |
| Examples | Input | Output |
| 02July04 | 2002 07 04 | |
| 02/07/04 | 2002 07 04 | |
| 05July04 | 2005 07 04 | |
| 05.07.04 | 2005 07 04 | |
| 2005July04 | 2005 07 04 | |
| 2005-07-04 | 2005 07 04 | |
| Remarks | If the input year is a two-digit value, it is assumed to be within the hundred year span with 2019 as the end of the span. For example, a year of 19 will be 2019, but a year of 20 will be 1920. | |
| Date/Time (DMY) Basic | ||
|---|---|---|
| Description | The Date/Time (DMY) Basic standardization definition standardizes dates that have format DMY HH:MM:SS. The output is a 4-digit year followed by a zero-padded two-digit month, followed by a zero-padded two-digit day, followed by a zero-padded two-digit hour, followed by zero-padded two-digit minutes, followed by zero-padded two-digit seconds. The day, month, and year are separated by spaces and the time elements are separated by spaces. The date and the time are separated by a "T". | |
| Examples | Input | Output |
| 04/07/02 | 2002 07 04 | |
| 15 Oct 1970 | 1970 10 15 | |
| 11 May 2000 10:12:45 | 2000 05 11T10 12 45 | |
| Remarks | The output of this definition is the same as Date/Time (MDY) Basic and Date/Time (YMD) Basic. | |
| Date/Time (DMY) Extended | ||
|---|---|---|
| Description |
The Date/Time (DMY) Extended standardization definition standardizes dates that have format DMY HH:MM:SS. The output is a 4-digit year followed by a zero-padded two-digit month, followed by a zero-padded two-digit day, followed by a zero-padded two-digit hour, followed by zero-padded two-digit minutes, followed by zero-padded two-digit seconds. The day, month, and year are separated by dashes and the time elements are separated by colons. The date and the time are separated by a "T". |
|
| Examples | Input | Output |
| 04/07/02 | 2002-07-04 | |
| 15 Oct 1970 | 1970-10-15 | |
| 11 May 2000 10:12:45 | 2000-05-11T10:12:45 | |
| Remarks | The output of this definition is the same as Date/Time (MDY) Extended and Date/Time (YMD) Extended. | |
| Date/Time (MDY) Basic | ||
|---|---|---|
| Description |
The Date/Time (MDY) Basic standardization definition standardizes dates that have format MDY HH:MM:SS. The output is a 4-digit year followed by a zero-padded two-digit month, followed by a zero-padded two-digit day, followed by a zero-padded two-digit hour, followed by zero-padded two-digit minutes, followed by zero-padded two-digit seconds. The day, month, and year are separated by spaces and the time elements are separated by spaces. The date and the time are separated by a "T". |
|
| Examples | Input | Output |
| 04/07/02 | 2002 04 07 | |
| Oct 15 1970 | 1970 10 15 | |
| May 11, 2000 10:12:45 | 2000 05 11T10 12 45 | |
| Remarks | The output of this definition is the same as Date/Time (DMY) Basic and Date/Time (YMD) Basic. | |
| Date/Time (MDY) Extended | ||
|---|---|---|
| Description |
The Date/Time (MDY) Extended standardization definition standardizes dates that have format MDY HH:MM:SS. The output is a 4-digit year followed by a zero-padded two-digit month, followed by a zero-padded two-digit day, followed by a zero-padded two-digit hour, followed by zero-padded two-digit minutes, followed by zero-padded two-digit seconds. The day, month, and year are separated by dashes and the time elements are separated by colons. The date and the time are separated by a "T". |
|
| Examples | Input | Output |
| 04/07/02 | 2002-04-07 | |
| Oct 15 1970 | 1970-10-15 | |
| May 11, 2000 10:12:45 | 2000-05-11T10:12:45 | |
| Remarks | The output of this definition is the same as Date/Time (DMY) Extended and Date/Time (YMD) Extended. | |
| Date/Time (YMD) Basic | ||
|---|---|---|
| Description | The Date/Time (YMD) Basic standardization definition standardizes dates that have format YMD HH:MM:SS. The output is a 4-digit year followed by a zero-padded two-digit month, followed by a zero-padded two-digit day, followed by a zero-padded two-digit hour, followed by zero-padded two-digit minutes, followed by zero-padded two-digit seconds. The day, month, and year are separated by spaces and the time elements are separated by spaces. The date and the time are separated by a "T". | |
| Examples | Input | Output |
| 04/07/02 | 2004 07 02 | |
| 1970 Oct 15 | 1970 10 15 | |
| 2000 May 11 10:12:45 | 2000 05 11T10 12 45 | |
| Remarks | The output of this definition is the same as Date/Time (DMY) Basic and Date/Time (MDY) Basic. | |
| Date/Time (YMD) Extended | ||
|---|---|---|
| Description |
The Date/Time (YMD) Extended standardization definition standardizes dates that have format YMD HH:MM:SS. The output is a 4-digit year followed by a zero-padded two-digit month, followed by a zero-padded two-digit day, followed by a zero-padded two-digit hour, followed by zero-padded two-digit minutes, followed by zero-padded two-digit seconds. The day, month, and year are separated by dashes and the time elements are separated by colons. The date and the time are separated by a "T". |
|
| Examples | Input | Output |
| 04/07/02 | 2004-07-02 | |
| 1970 Oct 15 | 1970-10-15 | |
| 2000 May 11 10:12:45 | 2000-05-11T10:12:45 | |
| Remarks | The output of this definition is the same as Date/Time (DMY) Extended and Date/Time (MDY) Extended. | |
| Name | ||
|---|---|---|
| Description | The Name standardization definition standardizes names of individuals. | |
| Examples | Input | Output |
| john donovan | John Donovan | |
| mister morrison junior | Mr Morrison, Jr | |
| Remarks | ||
| Organization | ||
|---|---|---|
| Description |
The Organization standardization definition standardizes organization names. |
|
| Examples | Input | Output |
| Robe River Iron Associates | Robe River Iron Associates | |
| Moffat Limited Australia | Moffat Ltd, Australia | |
| A.T.W.Products Sp. z o.o. | ATW Products SP ZOO | |
| Remarks | ||
In addition to the definitions listed on this page, all English-language locales also inherit all Global definitions.
|
Documentation Feedback: yourturn@sas.com |
Doc ID: QKBCI_EN_defs.html |