Managing Data Quality!

The inability of organizations to bring coherence and focus in the management of data quality is critically impacting business objectives.

Governance efforts, when driven by committee definitions and roles assignments, are under constant pressure to demonstrate their value.
Data quality tools, while providing tactical quality improvements, fail to answer the "so what?" question about data quality issues.
Enterprise Architecture and Master Data Management investments, while part of the solution, are themselves challenged by poor data quality.

So what are the options? How can you bring your organization to care about data quality? How can you turn Data Quality Management into something ... manageable?

In this presentation, Data Quality Strategist Mario Cantin will:

Present a pragmatic, quick payback, value based framework to Data Quality Management.
Describe what's needed to make IT projects accountable of data quality.
Outline how the data governance business case can be self-sustained when driven by data quality requirements.
Share success stories and key success factors.

Mario Cantin has been a data quality strategist for over 20 years. He is the founder and Chief data strategist of Prodago, a firm implementing Lean Data Governance in organizations. His down-to-earth approach to all aspects of data management has helped many organizations in the past two decades. He has played key data governance roles in multiple organizations including National Bank of Canada, Cirque du soleil, Standard Life insurance, Bell Mobility, Desjardins and Canadian National Railways. He has a unique ability to help organizations finding applied and sustainable ways to collaboratively manage and govern their data. A sought after speaker and a passionate communicator, Mario has been sharing his views on data governance, quality and value with multiple audiences in the past years.