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Integrating the MDM with the Data Warehouse What Goes Where Dallas, Texas September 9, 2009

Credera is a full service business and technology consulting firm. What is Credera? Credera is a full-service business and technology consulting firm. Working with Fortune 1,000 companies, medium-sized businesses, government organizations, and clients across a broad range ofindustries, we provi

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Integrating the MDM with the Data Warehouse What Goes Where Dallas, Texas September 9, 2009

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    1. Integrating the MDM with the Data Warehouse What Goes Where? Dallas, Texas – September 9, 2009

    2. Credera is a full service business and technology consulting firm What is Credera? Credera is a full-service business and technology consulting firm. Working with Fortune 1,000 companies, medium-sized businesses, government organizations, and clients across a broad range of industries, we provide the experience and commitment necessary to solve today's toughest business and technology challenges. Because it's not just about meeting expectations - it's about exceeding them. Founded in 1999, Credera is headquartered in Dallas, TX and hosts offices and staffing locations around the country, including Austin, Denver, and Seattle. For additional information, visit www.credera.com.

    3. AGENDA

    4. What is the MDM ? Master Data Management

    5. What are the parts of MDM compared to other Systems? Operational Systems CRM eCommerce Supply Chain Management Other ERP’s

    6. MDM Functionality and Processes MDM Basics Base Functionality Input Data Flow MDM Hub Concept Contact Data Model

    7. Clean Addresses, Build the Rules, Merge the Contacts, Profile what you found MDM Base Functionality Contact Method Cleansing and Standardization Address Standardization and Cleansing Phone Number format verification Email format and delivery verification Matching and Survivorship Rules Identifying and Merging Duplicate Persons/Organizations Data Profiling

    8. Contact Channel Cleansing and Standardization A primary capability of an MDM product is to standardize and cleanse addresses and other contact information. Sometimes this functionality it built into the MDM product, while other products use third party software to cleanse the addresses. Physical addresses are parsed into their individual components (e.g., street number, street name, street type, street direction, city, state, zip, county, country, etc). Then the address is standardized to USPS naming conventions. The standardized address is checked for deliverability and coded as deliverable or undeliverable. Geocoding is performed, and a latitude and longitude are appended to the address. Emails are checked for formatting and deliverability. Phone numbers are also standardized in format.

    9. Matching and Survivorship Rules Matching rules are built to determine when to merge persons and organizations. For example a rule might state “match on same first name, same middle name, same last name, and same street number/name”. A more relaxed rule might state “match on same first name, same last name, and same zip code”. Survivorship rules determine the preferred source for each attribute in the case of a merge. For example, a rule might require “phone numbers from the CRM, email addresses from the ecommerce system”. The preferred source for a particular attribute may also be defined. For example, phone numbers might be sourced in the order “CRM, then ecommerce, then Marketing Affiliate”, such that the phone number will be pulled from the CRM if it exists, the ecommerce system if it does not exist in the CRM, etc.

    10. Identify and Merge Duplicate Persons/Organizations One of the main capabilities of most MDM tools is to identify and merge duplicate records for persons and organizations. This consolidation creates one single, master record for each contact. The process of identifying duplicate records is a complex process. If the rules are too vague, then records may be over merged. Meaning, records that should not be merged may be incorrectly identified. If the rules too detailed then records may be under merged, and merges that should occur will be missed. The merge is performed after the cleansing and standardization using the matching rules. The attribute collection is performed using the survivorship rules.

    11. Data Profiling Most MDM tools also offer data profiling capabilities. Data profiling is the process of examining the data available in an existing data source and collecting statistics and information about the data. Some companies look at profiling as a way to involve business users in what traditionally has been an IT function. Domain Type Pattern Frequency Statistics Interdependencies

    12. How are Customers and Organizations stored in the MDM database?

    13. How is the Data Stored in MDM? The Contact Data Model

    14. How does data get into MDM ? The Input Data Flow

    15. Who uses the data in the MDM? MDM Hub Concept

    16. AGENDA

    17. How do we match customers in MDM with transactions in the Operational Systems?

    18. Customer Transactions in the Data Warehouse

    19. How do we match organizations in MDM with transactions in the Operational Systems?

    20. Organization Transactions in the Data Warehouse

    21. MDM “Over Cleansing” - Missing Customers/Organizations in the MDM

    22. AGENDA

    23. Where should we put our External Enrichment data attributes?

    24. Customer Enrichment

    25. Organization Enrichment

    26. Enrichment Attributes in the Data Warehouse

    27. Conclusion There are many different ways to integrate the Master Data Management (MDM) repository with the new or existing data warehouse. A best practice is to use the MDM as a hub for all attributes related to a person or organization. This enables operational systems to supply specific information to the MDM and subscribe to shared information in the MDM hub. Data enrichment can be performed by an enrichment partner and brought into the MDM hub to share with data subscribers. One or multiple data enrichment partners can be used for your customer and organizational data enrichment. The data warehouse is required to load the customer and organization dimensions from the MDM and match them with the transaction facts that are acquired from the operational systems. This matching is done through the cross-reference table in the MDM that associates the customer/organization keys in the operational system to the MDM keys . There may be missing persons or organizations in the MDM and specific business rules will need to be formulated on how to handle the transactions that are not associated with any MDM person/organization. The integration of the MDM with the data warehouse can be challenging, but the payoffs are worth the effort. There are countless benefits, both in cost savings and increased revenue, which can be attained from integrating clean, enriched customers/organizations from the MDM with the measurements that are contained in your data warehouse.

    28. Integrating the MDM with the Data Warehouse What Goes Where? Dallas, Texas – September 9, 2009

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