Whats New In Oracle Customer Hub 8.2 Version Dinesh Chandrasekar

Oracle Customer Hub V 8.2 New Features - Sierra Atlantic CRM & MDM Competency Whitepaper

What’s New in Oracle Customer Hub 8.2 v? It’s time to find
Your Golden Customer
Dears,

It’s been a while we talked about Master Data Management specially my favorite topic Golden
Customer Record. I am quiet excited about the new Oracle Customer Hub 8.2 v application and its
advanced features. For next few blogs I will be covering these features in details. Hope you will find this
useful.

Do you really know Your Customer?

Fragmented inconsistent Customer data hides revenue recognition, introduces risk, creates sales
inefficiencies, and results in misguided marketing campaigns and lost customer loyalty.. You’ve been
analyzing terabytes of customer data for years. You’ve told your customers and stakeholders that your
organization is customer-centric. But your customer data is unreliable and it’s affecting your ability to
retain customers, minimize fraud and manage privacy. According to Forrester, 92% of companies believe
having an integrated view of customer data is either “critical” or “very important.” Only 2% have actually
achieved that goal.
Why have only 2% of companies achieved a 360 Degree Customer view?

Because customer data integration (CDI) isn’t just about customer relationship management (CRM).
Customer data is often created and maintained in non-CRM systems, so different departments have
different view of the customer.
It isn’t about repurposing your data warehouse. A data warehouse is an analytical solution, not an
operational, transactional solution.
And it isn’t about building your own customer master application. That’s too risky–and expensive.
Building instead of buying will keep you mired in data model design for years.

Oracle Customer Hub (Siebel UCM)

Oracle Customer Hub (also known as Siebel Universal Customer Master or Siebel UCM) is Oracle’s lead
Customer hub solution. Oracle Customer Hub (OCH) leverages the unrivalled domain expertise of the
Siebel platform to deliver a rich and complete CDI solution with many unique capabilities. OCH’s
comprehensive functionality enables an enterprise to manage customer data over the full customer
lifecycle: capturing customer data, standardization and correction of names and addresses;
identification and merging of duplicate records; enrichment of the customer profile; enforcement of
compliance and risk policies; and the distribution of the “single source of truth” best version customer
profile to operational systems.

Oracle Customer Hub (OCH) 8.2 is a major release of the Customer master solution of the Oracle Master
Data Management (MDM) portfolio, probably one of the largest in several years. This release’s ambition
is to help organization turn their data into true corporate assets. It is focused on 3 major themes: best in
class data governance, end-to-end data quality, and pre-built integration.

By: Dinesh Chandrasekar, Practice Director CRM, BI & MDM CoE


Best in class data governance relates to
o The availability of the first tool of the market built to address the needs of Data
Governance professionals: Data Governance Manager
o A new module enabling best in class hierarchy management with the inclusion of
Hyperion Data Relationship Management within OCH providing analytical MDM and
hierarchy manipulations capabilities.
o MDM analytics
o Enhanced stewardship capabilities
End-to-end data quality provides a complete framework enabling controlled path to higher data
quality levels for the enterprise, the visible part of MDM projects
Pre-built integration through enhanced web services and Application Integration Architecture
provides faster deployments because MDM is pre-cabled to consuming apps made “MDM
Aware” .

New Enhanced Features of Oracle Customer Hub 8.2 V

Oracle Siebel OCH 8.2 includes a rich set of features providing an end-to-end data governance solution.
The key components that constitute data governance include
Data Governance Manager
Advanced Customer Hierarchy Management
MDM Analytics
List Import
Advanced Data Stewardship

Data Governance Manager (DGM)



DGM is a solution targeted to help organizations with the centralized administration of enterprise data
governance. It delivers a new web 2.0-like user interface that simplifies hub operations by enabling
organizations to easily monitor and track key hub data quality metrics and the sources of bad data, while
also allowing easy access to data repair operations. DGM has been built to meet the requirements of
data governance professionals especially in the area of
Define and communicate data definitions, policies and business rules
Operate consolidate, share and cleanse hub functions
Monitor hub operations and track sources of bad data in the enterprise
Fix data issues proactively and help tune data quality rules

Oracle Data Governance Manager (DGM) provides an intuitive graphical user interface as the single
management destination for data stewards and business users alike. Using DGM, data stewards can
easily perform stewardship operations on cross-departmental data in a centralized place. The DG
overseeing group can also manage the data stewards performance and workloads and generate data
quality assessments to monitor and demonstrate progress for continued executive support. DGM serves
as a place to define and set enterprise master data policies and to monitor and fix data issues. It also
helps operate the different functions in the MDM data lifecycle: Consolidate, Master, Cleanse, Share and
Govern, and is designed around these functions, giving easy access to them

Master
The Master section shows the number of records that have been created and/or updated within a given
period of time. DGM shows results for contacts and/or accounts and allowing for drill-down to individual
records. This information gives insight into the activity that has taken place in the MDM hub.

Consolidate
In Consolidate, DGM helps operate data consolidation tasks with a workbench that creates, manages
and monitors batch import activities. Data stewards are can start batch import jobs into the MDM hub
very quickly and directly from DGM. The steward can also view completed and pending jobs, as well as



perform any immediate correction of rejected records from a previously run batch job.

Cleanse
Poor data quality can increase the cost and complexity across the enterprise. DGM enables continuous
monitoring of data quality within the MDM hub by tracking data quality metrics around completeness,
at a record and attribute level. It shows the data quality level for the MDM hub and all registered
external system, allowing data stewards to monitor the data and identify bad sources of data that they
can then resolve accordingly.

Share
DGM shows detailed information on the MDM hub‟s real-time activity in its Share function. It shows the
number of updates, merges and unmerges that have happened in the system in a given period of time.

Govern
Governance involves keeping track of and defining data metadata and rules that will ultimately dictate
how the enterprise data runs. DGM provides a working queue for manual resolution cases for the data
steward. It also provides easy access to multiple administration and rule definition screens of the
customer hub. Additionally, DGM links to reference documents to view the agreed upon data
definitions. Finally, it acts as a dashboard to access data remediation tools, such as Data Watch and
Repair.

Data Relationship Management for Oracle Customer Hub – Advanced Customer Hierarchy
Management
Advanced Customer Hierarchy Management is enabled within OCH through integration with Oracle
Hyperion Data Relationship Manager (DRM). This expands hierarchy management capabilities with
DRM‟s features made available for UCM accounts, account hierarchies and Dun & Bradstreet (D&B)
hierarchies. In this advanced option, data stewards can create new hierarchies; drag and drop new
account nodes into and out of a hierarchy; and compare, blend, merge, and delete hierarchies.



With OCH 8.2, users can also edit hierarchies within DRM by clicking the Advanced Hierarchy
Management button. In a separate view, users select accounts from 3 places:

* UCM Account Hierarchies,
* UCM Accounts, and
* D&B Account Families.

Once selected, these hierarchies can be exported to DRM, where data stewards can use all DRM
features for hierarchy management and manipulation. While working in DRM, data stewards can:

* Create hierarchies: using UCM accounts that were selected and imported into DRM.
* View hierarchies: UCM hierarchies can be browsed and compared to one another. Additionally, each
account can be queried for and located across all hierarchies. Additional information on accounts within
a hierarchy includes: siblings, parent, ancestors, children, descendants and links.
* Edit hierarchies: Data stewards can insert and remove UCM accounts from a hierarchy, drag and drop
UCM accounts, and also delete, blend and merge hierarchies.

After performing changes in DRM, data stewards can return to OCH with the account hierarchies they
had previously selected and sent to DRM. All changes in the selected hierarchies, as well as any newly
created hierarchies in DRM, will be brought back to OCH upon committing a Save. This action also closes
the DRM session, and purges all Hub data from the DRM application. Also, the modified hierarchies are
versioned within OCH; in other words, the previous hierarchy version is stored as a History version and
the updated hierarchy will be displayed as the current Customer Hub account hierarchy.

MDM Analytics



MDM Analytics dashboards enable data steward to quickly and proactively assess the quality of
customer and contact dimensional data entering OCH. Through its ease of use, the dashboard
accelerates the data‟s time-to-value and helps to drive better business results by:

1. Pinpointing where data quality improvement is needed;
2. Enabling the data stewards to take corrective action to improve the quality and completeness of the
Customer and Contact data; and,
3. Helping to improve organizational confidence in the information.

Master Record Completeness Dashboard Page

The Master Record Completeness dashboard page presents the data steward(s) with a comprehensive
view of their organization‟s Customer and Contact data completeness. The data steward(s) is able to
quickly determine the state of their data quality and identify data entities. This helps to ensure that
organizations have all of the necessary intelligence data to make correct business decisions.

Accuracy Dashboard Page The Accuracy Dashboard page presents the data steward(s) with a view of the
activity against their Account and Contact in the system. This dashboard provides the data steward(s)
the means to quickly highlight the Customer and Contact records in their system requiring additional
attention.



List Import
Oracle OCH allows the business user to perform bulk import operations on Account and Contact records
from external systems with easier error management. This functionality is now aligned with the List
Import functionality of Siebel Marketing and can be deployed with or without mastering functionalities.
The configurable process allows the business user to import from the following file formats: Delimited
text files (such as csv, tab delimited, fixed width, or other delimiter), and XML files. The automated
process consists of two steps performed within OCH Administration screens and views: a list import into
OCH SDH (Source Data History) tables, and then a batch process which calls existing OCH services for
data cleansing, data matching and survivorship

OCH 8.2 delivers the following key benefits:
* Empowers business users to load data



o Configurable metadata driven approach
o Template driven approach
* Error resolution views
* List Import as a web service

Enhanced Stewardship OCH 8.2 Data stewardship capability has been enhanced to not only deliver
richer set of features but also to provides a better user experience. The new enhancements and
capabilities include:
Enhanced Survivorship
o Rules Engine Based survivorship to define any rule beyond the seeded Rule Types.
Survivorship rules are an automated means of controlling the quality of customer data
stored in UCM. Out of the box, we support integration with Siebel Business Rules Engine
(Haley) for Business logic based survivorship; integration with any other rules engine
can be configured
o New Rule Types – Master and Slave in merge case. Master means the Survivor record
selected by the user will win over the Victim record. Slave means the victim record
selected by the user will win over the survivor record. In UCM connector case, when
incoming request comes in, Master means the values stored in UCM will always win
over the incoming record. Slave means the values sent by external application into UCM
will always win over the values in the existing best version record.
o Configurable „Date Field enhancement enables customer to choose a different Date
field other than the default “Updated” field as the comparison criteria when
Recent/History comparison rules are executed.
o Household Survivorship can be configured

Enhanced Merge/Un-Merge
o Guided Merge using Task Based User Interface allows end-user to review duplicate
records and give ability to override the survivorship rules engine outcome in step by
step process. Guided merge results in three versions of record in action and allows end
user to decide how the final record version in the UCM should look like after the merge
task is submitted for process

 Survivor: The record whose row id will survive
 Victim: The record that will be deleted
 Suggested: Record generate as result of running through survivorship engine o

o Suspects – Incoming record posted to base table as Suspect awaiting Resolution. In
previous UCM release, when a new incoming record is flagged as potential duplicate of
existing records (manual review case), the new record is NOT created, and instead it is
placed in the “Incoming Duplicates” views, waiting for data steward intervention. When
Suspect Match feature is enabled, UCM will insert a new record for the manual review
case and continue processing, while flagging the record for review later in “Existing
Duplicates” views. Suspect record can be updated, deleted or merged via UI or
incoming message. Data Steward can choose to approve suspect or can merge into an
existing UCM record via Guided Merge or one step merge operation flag.



o Merge Request enhancement provide ability to submit merge request from edge
systems using Web Services for two existing records. Synchronous response on the
merge request status will be sent to the requestor, i.e. Pending, Rejected etc. Merge
requests on records not existing in UCM database will be rejected.
o Enhanced Un-Merge User interface to list only previously merged records.
--------------------------------------------------

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.



OCH - End-to-End Integration

Oracle OCH 8.2 is delivered with pre-built standards compliant and cross-industry-interoperable
integration processes with Siebel CRM, Oracle Ebusiness Suite, SAP and Oracle Billing & Revenue
Management to acquire customer data and share master data. There are 2 types of flows that are
supported with this pre integrated solution:

The Push Mode

In this mode of operation, the participating applications act passively where they send new or updated
customer information to the hub for cleansing, deduplication and enrichment. The hub then in turn
publishes the cleansed golden version to all the participating applications.

The push mode flows are asynchronous. This mode of operation is non-intrusive with respect to the
need to change the source and target applications. They do not assume that the hub is the data master,
thereby ensuring that the authoring can be decentralized. Because of the non-intrusive character of this
architecture, “push mode” MDM implementations can lead to faster MDM project delivery.

Pull Mode

In this mode of operation, Siebel CRM and Oracle EBS (and possibly other applications using
composite UI) interact with the hub in real time by executing synchronous integration
processes at the time of data entry



The Pull mode processes are synchronous and enable a real-time interaction between Siebel CRM,
Oracle EBS and OCH. Through these processes the consuming applications have On-Demand access to
the source of truth for customer data and hence allow duplicate data prevention and capture of the
right data at the time of entry The key enhancements with OCH 8.2 related to prebuilt integration
capability include

* Web Services Library
*Support for latest versions of Siebel, Ebusiness Suite, SAP and BRM
*Integration Process Interoperability

Web Services Library OCH 8.2 has been enhanced to include more than 20 additional
composite and granular web services. These services provide a handle to expose day to day
operational and analytical functionality used by Data Steward in form of web services.
Customer‟s preferable user interface applications can consume these services to expose this
functionality. Out of the box Oracle used ADF based application Data Governance Manager
consumed following web services.

Master Service

Following services are added in OCH 8.2 to expose master section functionality covered under
Data Governance Manager.
* Get Master Entities Count
*Get Master Organization Details
*Get Master Person Details

Consolidate Service



These services provide reports on exiting batches and help report records gone in exception
patch. We can leverage these services to make corrections and re-run the batches Following
services are added in OCH 8.2 to expose consolidate section functionality covered under Data
Governance Manager.

*Get Batch Process Report
* Get Specific Batch Report
* Get Completed Records Batch Report
* Get Organization Rejected Records Detail Report
* getPerRejectRecordsDetailReport
* updateOrgBatchRejectedRecords
* updatePerBatchRejectedRecords

ConsolidateListImportService
These services are very extensively used by consolidate module of DGM to kick of new import jobs.
Following services are added in OCH 8.2 to expose list import functionality over web service,
* obtainTemplateList
* submitNewImport

CleanseCompletenessService
These services help bad sources of data in the enterprise, and pull the records which are non complaint
with the completeness matrix defined. Following services are added in OCH 8.2 to expose cleanse
section functionality covered under Data Governance Manager.
* Get Hub Complete Compliance Info
* Get Hub Organization Incomplete Detail
* Get Hub Per Incomplete Detail
* Get Source Complete Compliance Info
* Get Source Organization Incomplete Detail
* Get Source Per Incomplete Detail

ShareService
This service helps get the real-time information about the share module functionality.
* Get Share Information

SystemsRegistrationService
This services helps get number of systems registered to OCH
* Get Systems Registration Info

GovernService
This service helps pull work queue information of Data Steward from OCH
* Get Organization Suspect Records
* Get Person Suspect Records
* Remove Pending Record
* Submit Merge Request Organization Record
* Submit Merge Request Person Record



Request Merge Services
These services can request merge on two selected records over the integration layer
* Organizations
* Persons

Siebel 8.1.1, EBS R 12, SAP and BRM Integration and Certification Prior to OCH 8.2, the participating
applications included Siebel CRM 8.0 and Oracle Ebusiness Suite 11.5. In OCH 8.2, the latest versions of
the participating applications (Siebel CRM 8.1.1 and Oracle Ebusiness Suite R 12) are supported. Prior to
OCH 8.2, the pre-integrated solution included only Siebel CRM and Oracle Ebusiness Suite. With OCH
8.2, additional applications are also integrated out of the box. The additional applications include Oracle
BRM 7.4 and SAP ECC.

Interoperability with Communications Industry PIPs The Customer master data management
integration processes now are interoperable with Communications Industry integration processes
supporting the following 2 scenarios:

Customer Creates: When a Customer Data is created in CRM as part of an Order it automatically
triggers a Sync flow that will publish the data to the Oracle Customer Hub. The Oracle Customer Hub
will process the data by cleansing it, matching to existing data, and if match is found linking it and
updating the golden record of the customer. OCH will then publish back to CRM the updated data
and publish to subscribing applications. In the meantime on the CRM side the CSR will complete the
Sales Order and submit it trough the AIACOM Order to Bill flow with a reference to the Customer
Data. The Sync Customer step will perform a Cross-reference check and identify that the Customer
Data is new and needs to be created in BRM. The new customer data will be queried from CRM and
used to create the Customer Data in BRM. The Oracle Product Hub will publish in batch mode to
BRM the updates that were applied to the Customer Data. The BRM connector will perform a Cross-
reference check. If the cross-reference is found, then the updates will be applied to BRM. If the
Cross reference is not found then they will be discarded.

Customer Updates (Account and Contact): When a CSR updates Account Data in CRM this
automatically triggers a Sync Customer flow that will publish the data to the Oracle Customer Hub
(as part of the Customer MDM flow) and to Oracle BRM (as part of the AIACOM Agent Assisted
Billing Care flow). OCH will process the data and do the usual cleanse, match, and link and update
and publish the updated data as response back to CRM and as sync to subscribing applications.
AIACOM Agent Assisted Billing Care flow will check if a BRM Cross Reference exists for the updated
account data and if so it will update the account in Oracle BRM. The Oracle Product Hub will publish
in batch mode to BRM the updates that were applied to the Customer Data. The BRM connector will
perform a Cross-reference check. If the cross-reference is found, then the updates will be applied to
BRM. If the Cross reference is not found then they will be discarded as the customer does not exist
in BRM and thus is a prospect



Contact Level Update of Customer Data: Oracle BRM only provides services to update a Contact in
the context of an Account. When OCH publishes a Sync Contact it needs be transformed into a Sync
Account message so that it can be processed by the BRM services. Compared to the previous flow,
the flow described in this slide has an additional transformations step that will convert the Sync
Contact Message into a Sync Account message, so that the Contact can be updated in the context of
the Account.

SOA Governance Tools Integration solution is delivered on Oracle‟s leading fusion middleware which
contains following SOA governance capabilities.

Artifact Generator: The Artifacts Generator is a development tool that can help jumpstart your Oracle
AIA development by auto generating much of the common code needed to create Oracle AIA application
business connector (ABC) service implementations. The Artifacts Generator is a command line Apache
Ant tool that uses the Free Marker template engine to generate complete and compliable ABC service
implementations in BPEL.
PIP Auditor: The Process Integration Pack (PIP) Auditor verifies that a PIP‟s design and development
adheres to Oracle Application Integration Architecture (AIA) guidelines. The PIP Auditor contains a
number of tests that check for different standards mandated or recommended by Oracle AIA with
respect to PIP design and development. The PIP Auditor generates high-level HTML and detailed XML
reports that provide information about violations to the mentioned standards
XMAN: The XSLT Mapping Analyzer is a tool you can use to generate the mapping information from the
application business connector (ABC) service transformation XSL into HTML.

The input of the XSLT Mapping Analyzer is the ABC service transformation XSLT. The ABC service
transformation XSLT is an XSL code that maps the source enterprise business message (EBM) to
application schema or from application schema to EBM. To simplify the mapping from the source
application schema to the target application schema, the XSLT Mapping Analyzer takes the XSLT file as
input and extracts the mappings from the source to target elements and displays the mapping
information in a table that is easier to understand.


Whats New In Oracle Customer Hub 8.2 Version Dinesh Chandrasekar

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