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New York Marriott Marquis

1535 Broadway
New York, New York 10036

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Sunday, October 14, 2012

1:00 PM - 3:00 PM


Sunil Soares, Founder & Managing Partner, INFORMATION ASSET LLC.

Data Governance requires strong buy-in from the business to treat information as an enterprise asset. As a result, data governance practitioners need to articulate data governance in terms that matter to business users. For example, poor data quality manifests itself in the form of duplicate customer records in a bank, which affects the ability of the credit risk group to establish the overall exposure to an individual customer across product lines. In retail, poor data quality results in duplicate mailings of multiple catalogs by the marketing department to the same household.

At the same time, data governance leaders are under tremendous pressure to show tangible ROI quickly. Given these financial pressures, data governance leaders need to re-use existing best practices. If a particular data governance organization has worked in other banks, then use it as a blueprint instead of starting from scratch. If other retailers have experienced specific data quality issues, then use those critical data elements as a starting point. If other manufacturers have successfully used a RACI matrix to manage their product master data, then start with that artifact.

Come to this session if you want to learn about data governance artifacts that can jumpstart your program and put you on a path to faster ROI.

This tutorial is based on Sunil Soares’s books Selling Information Governance to the Business: Best Practices by Industry and Job Function (MC Press, 2011) and Big Data Governance: An Emerging Imperative (MC Press, 2012). The tutorial is divided into five parts:

1. Sample business cases by industry that deal with the application of data governance principles within banking and financial markets, insurance, healthcare, manufacturing, retail, travel and transportation, government, oil and gas, telecommunications, and utilities.

2. Sample business cases by job function that deal with the application of data governance principles within critical job functions such as sales and marketing, finance, information technology operations, information security and privacy, human resources, legal and compliance, operations, supply chain, and product management.

3. Sample data governance artifacts such as a data governance organization, RACI matrix, data quality metrics, and critical data elements by industry to help you jumpstart your program without starting from scratch.

4. Process Data Governance use cases that map data governance policies to specific steps in key business processes such as claims processing and equipment maintenance.

5. Big Data Governance will be covered at a high level to discuss how data governance programs can introduce big data into existing frameworks for organization, stewardship, metadata, and data quality.

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