Dears,Lets see the E2E Data quality features that are available with OCH 8.2 V.
OCH End to End Data Quality
Oracle Customer Hub provides best in class data quality capabilities with a complete offer covering profiling, address validation, parsing and standardization and deduplication (including an ability to support multimode –real time and batch-, multi address, multi languages, multi source systems and more generally multi criteria matching rules), as well as a data decay engine.
Oracle Data Quality provides a framework enabling a controlled path to higher data quality levels for the hub as well as the entire enterprise Data quality rules are defined declaratively in the Rules Manager and executed against the source systems‟ inputs in the Rules Execution Engine (aka Workbench) to profile / analyze the data with pre-defined metrics, cleanse and standardize the data including the validation and potentially the correction of invalid addresses, match and deduplicate duplicated records and finally enrich the data from 3rd party systems. The objective of this framework is to load the target system with zero rejects and a clean customer data set.
The exception management layer’s goal is to provide a framework to both automatically or manually fix the incorrect data not only in the target CRM/MDM system but also in the sources and hence enhance data quality for the enterprise. Data quality levels can be gradually increased / adjusted as a function of the capacity of the exception management process and the time at hand to fix the data given project constraints.
Integrated Cleansing
Oracle Data Quality Address Validation Server provides capabilities to parse, standardize, transliterate, deduplicate and validate all address data, resulting in improved address data quality, which in turn would help enterprise in integrating international customer information, preventing against identity loss, and assisting in fraud detection and prevention, as well as directly reducing mail based marketing costs. Oracle Data Cleansing Server performs validation of address data against published standards and directories by utilizing reference data. As postal codes change in different countries due to settlements, system changes or name changes, reference tables for each country can also be updated on a monthly, quarterly or biannual basis. Oracle leverages arrangements with leading postal reference data provider to enable customers to receive the updates on a periodical basis. These reference tables are provided in a separate, platform-independent database making it easily updateable at any time.
Enhanced Matching
Oracle Data Quality Matching Server performs high-quality search, match, duplicate identification, and relationship linking on all types of name, address and identification data.
The highlights of the Oracle Data quality Matching server include:
* Multi-Mode support
Oracle Data Quality Matching Server provides the capability to use different set of match rules depending on the mode of operation. For example, it allows one set of match rules to be applicable for data getting in through Real time mode and a different set of match rules for data getting in through the batch mode.
* Multi-Source support
Oracle Data Quality Matching Server provides the capability to use different set of match rules depending on the Source from where the data is coming from. For example, it allows one set of match rules to be applicable for data getting in from a CRM system and a different set of match rules for data getting in from EBIZ system.
* Multi-Attribute support
Oracle Data Quality Matching Server provides high quality search & matching on all types of name, address and identification data like:
o Person Names
o Organization Names
o Address elements
o Dates
o Telephone numbers
o Product Names
o Social Security/Drivers License/Passport Numbers etc.
The attributes/fields that are used for matching can easily be modified by changing the match fields in the system definition file. Also depending on the Business Requirement, different weighs can be given to different match fields.
* Multiple Address matching support Oracle Data Quality Matching Server provides the capability to consider all the addresses associated with the parent entity (Account or Contact) for matching as against using only the primary address for matching.
* Multi-Language support Oracle Data Quality Matching Server provides the capability to use different set of match rules depending on the Language or the Country of the record. This feature can be used by the Customers with multi geographical implementations where there will be the need to use different Search Criteria/Match Rules for records with different Languages/Countries. For example, a Contact with name „William‟ will match to a Contact with name „bob‟ when the country of the record is USA, but when the country of the record is India, „William‟ will not match to „Bob‟
* Multi Criteria (Rules Based) It includes an easy to use administration console which enables enterprise to create new match rules or edit existing match rules for their specific scenarios, or to extend matching to additional languages and/or locales. Oracle Data Quality Matching Server delivers industry leading global coverage with language/locale specific matching libraries for 52 languages/locales
* Support for highly flexible search strategies The solution includes highly-flexible search strategies, which can be selected based on the data being searched for, the level of risk and the need that the search must satisfy, allowing users to balance performance and comprehensiveness of search/match. There are multiple Search strategies like Extreme, Exhaustive, Typical, Narrow, and Custom that are available out of the box.
* Smart indexing to cut through error and variation in identity data, including multi-country, multi-language information. Using smart indexing and key building, Oracle Data Quality Matching Server cuts through error and variation (including spelling, phonetic, transliteration and multi-country data errors, as well as any missing or out-of-order words and other variations), to help enterprise discover duplicates and establish relationship both in real time and batch. There are multiple indexing strategies like Standard, Limited, Extended that are available out of the box.
* Support for Incremental Data Load
Oracle Data Quality Matching Server provides the capability to load and index the data incrementally rather than loading and indexing millions of data in one go. This will simplify the deployment of the solution.
Data Decay Management
Data decay refers to the way in which managed information becomes degraded or obsolete or stale over time. OCH 8.2 provides data decay dashboards to monitor and fix the data decay of Account and Contact records. These dashboards are accessed through the OCH administration screens. The below Data Decay chart shows number of Account in the hub with respect to corresponding Data Decay Indicator (DDI) value. DDI is an integer variable we use to track how stale is field values in our system. DDI values range from 0 to 100. 100 is the most up to date field and 0 is decayed field value. Every field which is tracked for Data decay resets the value of DDI to 100. Algorithm to reduce the DDI over period of time very configurable and can be tailed to customer needs on how quickly or slowly we want to make field values as stale.
OCH Data Decay management consists of the following key components:
* Decay Detection: Captures updates on the monitored attributes / relationships of a record and sets the decay metrics at the attribute level granularity or relationship level granularity.
* Decay Metrics Re-Calculation - Process to retrieve Decay Metrics for the monitored attributes/relationships of a record, use a set of predefined rules to calculate the new metrics value and update the metrics.
* Decay Correctness - Identifies stale data based on certain criteria and triggers a pre-defined action. Data decay monitors can be configured on column and records level. And can trigger actions based on some pre set criteria for example we can make a rule that when data is decay indicator for consumer address field reaches 80 then we automatically trigger enrichment call to Acxiom to get the latest information about the consumer address.
* Decay Report - generates Decay Metrics charts on a periodic basis
* Data decay dashboards enables the users to fix the right data at the right time thereby minimizing the cost of correction and enrichment of data.
Oracle data quality solution has a proven track record in terms of scalability and performance, handling large volume, highly-scalable, critical applications. The key enablers include
• Enhanced connector with Session Pool Management
· Enhanced index management that enables faster synchronization and incremental load support. · It is a highly-scalable solution with proven performance on systems with billions index entries on one database and millions real-time transactions in an hour.
Oracle Customer Hub provides best in class data quality capabilities with a complete offer covering profiling, address validation, parsing and standardization and deduplication (including an ability to support multimode –real time and batch-, multi address, multi languages, multi source systems and more generally multi criteria matching rules), as well as a data decay engine.
Oracle Data Quality provides a framework enabling a controlled path to higher data quality levels for the hub as well as the entire enterprise Data quality rules are defined declaratively in the Rules Manager and executed against the source systems‟ inputs in the Rules Execution Engine (aka Workbench) to profile / analyze the data with pre-defined metrics, cleanse and standardize the data including the validation and potentially the correction of invalid addresses, match and deduplicate duplicated records and finally enrich the data from 3rd party systems. The objective of this framework is to load the target system with zero rejects and a clean customer data set.
The exception management layer’s goal is to provide a framework to both automatically or manually fix the incorrect data not only in the target CRM/MDM system but also in the sources and hence enhance data quality for the enterprise. Data quality levels can be gradually increased / adjusted as a function of the capacity of the exception management process and the time at hand to fix the data given project constraints.
Integrated Cleansing
Oracle Data Quality Address Validation Server provides capabilities to parse, standardize, transliterate, deduplicate and validate all address data, resulting in improved address data quality, which in turn would help enterprise in integrating international customer information, preventing against identity loss, and assisting in fraud detection and prevention, as well as directly reducing mail based marketing costs. Oracle Data Cleansing Server performs validation of address data against published standards and directories by utilizing reference data. As postal codes change in different countries due to settlements, system changes or name changes, reference tables for each country can also be updated on a monthly, quarterly or biannual basis. Oracle leverages arrangements with leading postal reference data provider to enable customers to receive the updates on a periodical basis. These reference tables are provided in a separate, platform-independent database making it easily updateable at any time.
Enhanced Matching
Oracle Data Quality Matching Server performs high-quality search, match, duplicate identification, and relationship linking on all types of name, address and identification data.
The highlights of the Oracle Data quality Matching server include:
* Multi-Mode support
Oracle Data Quality Matching Server provides the capability to use different set of match rules depending on the mode of operation. For example, it allows one set of match rules to be applicable for data getting in through Real time mode and a different set of match rules for data getting in through the batch mode.
* Multi-Source support
Oracle Data Quality Matching Server provides the capability to use different set of match rules depending on the Source from where the data is coming from. For example, it allows one set of match rules to be applicable for data getting in from a CRM system and a different set of match rules for data getting in from EBIZ system.
* Multi-Attribute support
Oracle Data Quality Matching Server provides high quality search & matching on all types of name, address and identification data like:
o Person Names
o Organization Names
o Address elements
o Dates
o Telephone numbers
o Product Names
o Social Security/Drivers License/Passport Numbers etc.
The attributes/fields that are used for matching can easily be modified by changing the match fields in the system definition file. Also depending on the Business Requirement, different weighs can be given to different match fields.
* Multiple Address matching support Oracle Data Quality Matching Server provides the capability to consider all the addresses associated with the parent entity (Account or Contact) for matching as against using only the primary address for matching.
* Multi-Language support Oracle Data Quality Matching Server provides the capability to use different set of match rules depending on the Language or the Country of the record. This feature can be used by the Customers with multi geographical implementations where there will be the need to use different Search Criteria/Match Rules for records with different Languages/Countries. For example, a Contact with name „William‟ will match to a Contact with name „bob‟ when the country of the record is USA, but when the country of the record is India, „William‟ will not match to „Bob‟
* Multi Criteria (Rules Based) It includes an easy to use administration console which enables enterprise to create new match rules or edit existing match rules for their specific scenarios, or to extend matching to additional languages and/or locales. Oracle Data Quality Matching Server delivers industry leading global coverage with language/locale specific matching libraries for 52 languages/locales
* Support for highly flexible search strategies The solution includes highly-flexible search strategies, which can be selected based on the data being searched for, the level of risk and the need that the search must satisfy, allowing users to balance performance and comprehensiveness of search/match. There are multiple Search strategies like Extreme, Exhaustive, Typical, Narrow, and Custom that are available out of the box.
* Smart indexing to cut through error and variation in identity data, including multi-country, multi-language information. Using smart indexing and key building, Oracle Data Quality Matching Server cuts through error and variation (including spelling, phonetic, transliteration and multi-country data errors, as well as any missing or out-of-order words and other variations), to help enterprise discover duplicates and establish relationship both in real time and batch. There are multiple indexing strategies like Standard, Limited, Extended that are available out of the box.
* Support for Incremental Data Load
Oracle Data Quality Matching Server provides the capability to load and index the data incrementally rather than loading and indexing millions of data in one go. This will simplify the deployment of the solution.
Data Decay Management
Data decay refers to the way in which managed information becomes degraded or obsolete or stale over time. OCH 8.2 provides data decay dashboards to monitor and fix the data decay of Account and Contact records. These dashboards are accessed through the OCH administration screens. The below Data Decay chart shows number of Account in the hub with respect to corresponding Data Decay Indicator (DDI) value. DDI is an integer variable we use to track how stale is field values in our system. DDI values range from 0 to 100. 100 is the most up to date field and 0 is decayed field value. Every field which is tracked for Data decay resets the value of DDI to 100. Algorithm to reduce the DDI over period of time very configurable and can be tailed to customer needs on how quickly or slowly we want to make field values as stale.
OCH Data Decay management consists of the following key components:
* Decay Detection: Captures updates on the monitored attributes / relationships of a record and sets the decay metrics at the attribute level granularity or relationship level granularity.
* Decay Metrics Re-Calculation - Process to retrieve Decay Metrics for the monitored attributes/relationships of a record, use a set of predefined rules to calculate the new metrics value and update the metrics.
* Decay Correctness - Identifies stale data based on certain criteria and triggers a pre-defined action. Data decay monitors can be configured on column and records level. And can trigger actions based on some pre set criteria for example we can make a rule that when data is decay indicator for consumer address field reaches 80 then we automatically trigger enrichment call to Acxiom to get the latest information about the consumer address.
* Decay Report - generates Decay Metrics charts on a periodic basis
* Data decay dashboards enables the users to fix the right data at the right time thereby minimizing the cost of correction and enrichment of data.
Oracle data quality solution has a proven track record in terms of scalability and performance, handling large volume, highly-scalable, critical applications. The key enablers include
• Enhanced connector with Session Pool Management
· Enhanced index management that enables faster synchronization and incremental load support. · It is a highly-scalable solution with proven performance on systems with billions index entries on one database and millions real-time transactions in an hour.
Hope this is useful and we will see the Integration enhancement in my next blog artice
Your P&C
DC*
Nice post!!very informative
ReplyDeleteSo oracle data quality matching server is nothing but IIR, correct me if I am wrong.
Can we integrate IDQ with OCH too?We would need to do some cleansing on non address columns too