ORACLE DATA QUALITY KEY BENEFITS Oracle Data Quality offers, A complete solution for all customer data quality needs covering the full spectrum of data quality functionalities Proven scalability and high performance Unparalleled ease of use with an intuitive user interface Best-in-class matching engine with superb accuracy on all types of name, address and identification data, flexible and adaptive to suit any customer situations Unprecedented global coverage with matching libraries for 52 languages and address validation across 240 countries, 40 character sets and 100+ address formats Ability to do multiple-address, multi source, multi-mode matching using hybrid matching algorithms Tight integration with Oracle MDM and CRM applications to help customers understand the data quality status, address the data quality problems and achieve single view of the customer data Oracle Data Quality (ODQ) enables customers to execute all their data quality processes on their customer data. The product family combines powerful data analysis, cleansing, matching, as well as reporting and monitoring capabilities with unparalleled ease of use. ODQ Matching Server uses hybrid matching algorithms, giving it best-in-class match accuracy. ODQ Address Validation Server offers support for more than 240 countries. Together with the profiling and standardization functionality, ODQ is a truly complete solution for all data quality needs within an enterprise, delivering in terms of both performance and scalability on a global scale. OVERVIEW Oracle Data Quality (ODQ) products include powerful data analysis, parsing and standardization, address validation and matching, as well as reporting and monitoring functionalities. Customers can use ODQ to profile data on their external sources, as well as parse and standardize unstructured data into key customer attributes beforehand, ensuring improved accuracy in the matching and deduplication steps. Moreover, with a best-in-breed matching server embedded, users can match and identify duplicate customer records based on key customer attributes across 52 languages. ODQ offers a pre-built integration with the address validation server which covers more than 240 countries. Together, these tools give ODQ an unprecedented global coverage. The solution has a proven track record in terms of scalability and performance, handling large volume, highly-scalable, critical applications. Additionally, with its intuitive user interface, ODQ puts control of data quality processes in the hands of business information owners, such as data analysts and data stewards. Oracle Data Quality Profiling Server When data quality is measured, it can be effectively managed. Data profiling is the first step for data quality. ODQ Profiling Server gives users with the ability to measure the level and nature of data quality problems across multiple data sources to identify, quantify, and categorize current and potential data quality issues and adherence to business rules. Additionally, the product s powerful and easy to read reports offer drill-down functionality allowing users to view the underlying data associated with each data quality problem. The product also provides the metrics and reports that business information owners need to continuously measure, monitor, track, and improve data quality at multiple points across the organization. 1
Oracle Data Quality Parsing and Standardization Server The goal of the standardization phase of a data quality management process is to remove or flag problems prior to moving on to the matching phase. ODQ Parsing and Standardization Server can also generate metadata that enables easy parsing and standardization of data. In the standardization phase each of the key data fields is passed through a series of user defined rules to remove inconsistencies and unconformities identified during the data profiling stage. The output is a range of new data fields containing standardized and enhanced data. The new data fields created during the standardization phase may be used solely for the matching process, or they may also be written back to the original source file to replace the original data. Some examples of tasks carried out by this module include noise removal; data parsing (e.g. name, address, descriptions); standardization of terms (e.g. use of dictionaries to correct common misspellings etc., or use of transforms to standardize date or telephone number formats); derivation of missing data values (e.g. derivation of gender from first name or title); or generation of data quality flags for use in matching rules e.g. records with multiple incomplete or invalid values can be flagged. Developing standardization rules using this product is fast and easy to understand using point and click components that leverage the data quality metadata generated during the profiling phase. It is highly flexible so users can define any number of output data fields and build multiple layers of data cleansing rules for each field. Finally, the embedded dictionary manager enables easy lookup of user created dictionaries within the product or third-party tables stored in other systems. Oracle Data Quality Matching Server ODQ Matching Server performs high-quality search, match, duplicate identification, 2
and relationship linking on all types of name, address and identification data. The solution includes highly flexible search strategies, which can be selected based on the data being searched for, the level of risk and the particular use case that the search must satisfy, allowing users to balance performance and exhaustiveness of the search and match task. ODQ Matching Server delivers industry leading global coverage with language and locale specific matching libraries for 52 languages or locales. It also includes an easy to use administration console, enabling an enterprise to adapt matching rules and algorithms for specific scenarios, and to match on multiple languages or locales. To enable a seamless deployment of data quality and management capabilities within an enterprise, ODQ Matching Server comes pre-integrated into Oracle CRM/MDM solutions. Additionally, it is a highly-scalable solution with proven performance on systems with billions index entries on a single database and millions of real-time transactions in an hour. Some highlights of the ODQ Matching Server functionality includes: Multi-Mode / Multi-Source support: ODQ Matching Server provides the capability to use different set of match rules depending on the operation mode. For example, it allows one set of match rules to be applied for real-time data loads and a different set of rules for batch loads. Similarly, it applies different match rules to data coming in from a CRM system versus data from an EBS source. Multi-Attribute matching support: ODQ Matching Server provides high quality search & matching on all types of name, address and identification data, such as: person names, organization names, address elements, dates, telephone numbers, product Names and identification numbers (e.g. social security, driver s license, or passport numbers). The attributes used for matching can be easily configured and different weights can be given to each attribute. Multiple Address matching support: ODQ Matching Server can take into account all the addresses associated with a given parent entity (i.e. account or contact) for matching. Multi-Language support: ODQ Matching Server provides the capability to use different sets of match rules depending on the language or country of the record. This feature is useful for multi-geographical implementations where 3
your business needs to use different search criteria and match rules depending on the country. Incremental Data Load: ODQ Matching Server can load and index the data incrementally rather than loading and indexing millions of data in a single batch. This simplifies the deployment and performance of the solution. Oracle Data Quality Address Validation Server ODQ Address Validation Server parses, standardizes, transliterates, deduplicates and validates all address data to achieved improved data quality in addresses, which, in turn, can help enterprises integrate their multinational customer information, prevent identity loss, perform fraud detection and prevention, as well as directly reducing mail-based marketing costs. ODQ Address Validation Server can parse both structured and unstructured address data by identifying address components and residue, and then standardizing the data all without the need for reference data. Subsequently, addresses are validated against published standards and directories by utilizing reference data. Since 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 providers to enable customers to receive the updates on a periodic basis. These reference tables are provided in a separate, platform-independent database making it easy to update at any time. ODQ Address Validation Server provides unparalleled international support with coverage of address data from over 240 countries. Moreover, the particular challenges from transliterating between different languages, especially with Asian languages, are overcome by performing string mapping for 40 different character sets and 7 alphabets. All these features are integrated into a single, easy-to-use interface, which allows users to add new countries without additional programming. ODQ Address Validation Server provides the following key capabilities: Advanced Validation, Parsing, Standardization and Updates: Validates the address against the country s postal reference file. The output details depend on the level of detail in the postal reference file. The validation status indicates 4
Oracle DQ Profiling Server Use business rules and reference data to analyze and rank data Identify, categorize, and quantify low-quality data Create reports and dashboards to confirm data quality improvement Oracle DQ Parsing and Standardization Server Use business rules to parse or merge data elements into the expected attributes for the master records Use reference data dictionaries to standardize freeform text data elements whether the address was valid, and if not, whether it has been corrected. During validation, the address is first parsed and validation can occur in both suggest and certify modes. In suggest mode, the engine suggests the best matched address. In Certify mode, extended address attributes (e.g. zip + 4-digit extension) are used to enrich the address. Supports address coverage in more than 240 countries Scalable high performance Integrated single engine supports all countries in both real-time and batch modes Metadata driven modulation of address validation New connector between Oracle Customer Hub (OCH 8.2) and ODQ Address Validation Server Oracle DQ Address Validation Server offers, Quick validation and correction of worldwide postal addresses Address coverage in more than 240 countries Integrated single vendor single API supports all countries Oracle DQ Matching Server Add real-time search for people, companies, contacts, addresses, households, titles and products Discover duplicates and establish relationships in real time Build relationship link tables and match external files and databases Copyright 2011, Oracle. All Rights Reserved. This document is provided for information purposes only, and the contents hereof are subject to change without notice. This document is not warranted to be error-free, nor is it subject to any other warranties or conditions, whether expressed orally or implied in law, including implied warranties and conditions of merchantability or fitness for a particular purpose. We specifically disclaim any liability with respect to this document, and no contractual obligations are formed either directly or indirectly by this document. This document may not be reproduced or transmitted in any form or by any means, electronic or mechanical, for any purpose, without our prior written permission. Oracle, JD Edwards, PeopleSoft, and Siebel are registered trademarks of Oracle Corporation and/or its affiliates. Other names may be trademarks of their respective owners. 5