Tony Brownlee

Partner, Head of Data Science and Research
Kingland Systems

Tony Brownlee is a Kingland Systems partner, responsible for leading and setting the strategy for the company’s Data Solutions business, including Kingland’s Data Science and Research operation and data quality and master data management (MDM) products and services. Mr. Brownlee has been instrumental in the creation of the Data Solutions business and has managed numerous operational, product development, business development, and client relationships for the company. Additionally, Mr. Brownlee manages Kingland Systems strategic relationship with IBM for Information Management software and other corporate marketing and business development functions. Mr. Brownlee is recognized as a thought leader in the financial services industry and speaks regularly at industry events on MDM, data governance, data standards, entity and hierarchy data. Within the industry, Mr. Brownlee has served on various committees including the Securities Industry Financial Markets Association (SIFMA); the International Standards Organization (ISO); the Financial Stability Board (FSB) for the Legal Entity Identifier (LEI); and the Enterprise Data Management Council (EDMC). Prior to joining Kingland Systems, Mr. Brownlee worked in the financial services industry providing consulting services for a top ten global bank and an international agri-business company. Mr. Brownlee holds a Bachelor of Arts degree in economics from Central College in Pella, Iowa; an MBA from Iowa State University; and serves on advisory boards of both institutions.

Check out the incredible speaker line-up to see who will be joining Tony.

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Data Management Operations to Add Value and Meet Regulatory Obligations

Wednesday, August 12th, 2015

16:45 Panel Discussion | Working Toward Better Data Quality for Better Decision Making

There is inherent business value in having data with integrity and improved data quality in any organization generates better business decisions. How do you determine the rules around data quality? How do you define KPIs and metrics around reporting?
Data quality experts will discuss:
• How can processes be automated to reduce costs and benefit in better reporting and data quality?
• How are data quality activities judged and managed when there are diverse divisions?
• How are business processes being improved to ensure data quality up front when it is captured?