SAP Data Quality Management
Transform enterprise data into a trusted, relevant, and everready resource for business insight. Empower business users to access and analyze the quality of their data for better decision making.
ZIP + 4®
carrier routes
eLOT®
DPV®
LACSLink®
SuiteLink®
RDI™
Address-level geocoding
Parcel-level geocoding
‘Last line’ data is data which provides city, province, country, and postcode.
Intelligent cleansing & enhancement for names
Data matching within & between data sources
Corporate & consumer householding
Build trust in your data
Reveal a single version of the truth by cleaning your dirty data. Define and standardize data with built-in address and data cleansing to uncover quality issues, expose hidden problems, and identify untapped relationships.
Enable unlimited scalability and high availability.
Improve performance and scale from one server to many to meet high-volume data needs with parallel processing, grid computing, and bulk data loading. Design data services to run in a top-down, right-to-left manner to execute queries automatically with multiple parallel threads. You can also execute the same job – whether in multiple parallel processes on one server or with multiple servers – to improve performance.Treat your data as a high-value asset.
Secure data access with a public key and maintain data relevance and relationships while keeping sensitive information confidential, anonymous, and compliant. Support encryption, decryption, and masking as part of the regular transformation of the extract, transform, and load (ETL) process.Stay connected to most data sources.
Leverage native support for most data sources including, Microsoft SQL Server, IBM DB2, IBM Informix, Oracle, HP Vertica, MySQL, Netezza, SAP Sybase, SQL Anywhere, ODBC, Persistent Cache, Attunity Connector, Flat Files and adapters for Apache Hive, HTTP, JDBC, JMS, MongoDB, and OData.
Ready-to-use Transformations
Transforms that help you improve the quality of your data and perform data movement operations. These transforms can parse, standardize, correct, enrich, match and consolidate your customer and operational information assets.
1. Global Address Cleanse (GAC) tranform.
Cleanse addresses from over 230 countries.Full address data for 40 countries - including house number, apartment/suite number, street, city/region, state, country and postcode
Last line address for 230+ countries - including city, province, country, and postcode
2. USA Regulatory Address Cleanse (URAC) transform.
Cleanse US addresses for verification and deliverability.USPS CASS Address Cleansing - cleanse your address data by checking against the authoritative USPS® CASS™ directory
USPS National Change of Address (NCOA) - support for NCOALink® 18-month End User Mailers (EUM), Limited Service Providers (LSP) or 48-month Full Service Providers (FSP)
USPS Delivery Sequence (DSF2) - achieve the highest level of address quality leveraging supplemental information supplied by USPS® postal carriers
3. Geocoder transform.
Transform physical mailing addresses into precise latitude and longitude coordinates, plus other enhancements.Address-level latitude-longitude geocodes
Parcel-level latitude-longitude geocodes
U.S. Census TIGER/Line data
4. Data Cleanse transform.
Parse, standardize, and cleanse all types of data - with intelligent cleansing options for:User defined pattern matching
Filters with boolean expressions
User Modifiable Dictionaries
Firm acronyms, nicknames, prenames, & gender codes
Emails, account numbers, phone numbers, & more
5. Match transform.
Data matching, deduplication, householding, and data consolidation.Data matching within & between data sources
Corporate & consumer householding
Deterministic and probabilistic matching algorithms
Confidence scores with custom weights
Logical AND/OR expressions
Platform Transforms
Transforms that are needed for general data movement operations. These transforms allow you to generate, map and merge rows from two or more sources, create SQL query operations (expressions, lookups, joins, and filters), perform conditional splitting, and so on.
1. Case.
Simplifies branch logic in data flows by consolidating case or decision making logic in one transform. Paths are defined in an expression table.2. Map Operation.
Modifies data based on current operation codes and mapping expressions. The operation codes can then be converted between data manipulation operations.3. Merge.
Unifies rows from two or more sources into a single target.4. Query.
Retrieves a data set that satisfies conditions that you specify. A Query transform is similar to a SQL SELECT statement.5. Row Generation.
Generates a column filled with integer values starting at zero and incrementing by one to the end value you specify.6. SQL.
Performs the indicated SQL query operation.7. Validation.
Ensures that the data at any stage in the data flow meets your criteria. You can filter out or replace data that fails your criteria.8. Entity Extraction.
Extracts information (entities and facts) from unstructured data and creates structured data that can be used by various business intelligence tools.
Enterprise Connectors
Deploy data quality capabilities with pre-built data quality connectors designed for easy plug-in integration.
SAP® DQM for SAP Applications.
SAP® Data Quality Management software, version for SAP solutions, helps you manage the quality of your information in enterprise resource planning (ERP), customer relationship management (CRM), and master data governance (MDG) software from SAP.SAP® DQM for Siebel® Applications.
SAP® DQM for Siebel CRM & UCM Connector leverages the SAP® Data Quality Management software platform to enable both real-time and batch address cleansing and duplicate detection for Siebel CRM & UCM systems.
Frequently asked questions about SAP Data Quality Management
How often are your geocodes updated?
Our geocode directories are updated monthly by industry-leading geocode data providers.
Ready to get started?
Request a demo or talk to our sales team to answer your questions about SAP Data Quality Management