Effective Data Classification Is Critical for Data Governance

Data is the raw inventory in today’s Data Factories. Data comes in all types, grains, and levels of complexity. Like in any factory, inventory needs to be managed. This is true of widgets and it is certainly true of data. Data inventory management begins with classification. Classification requires identification, tagging, then grouping data into like subject areas. Associating the subject areas to the business and technology landscape is part of the overall governance metadata framework. Once tagged, we require precise awareness of location and availability. We also need to capture the risk levels such as confidentiality or PII tags. We can optimize data inventory to have just the right amount, at the right time, and in line with minimum quality standards. This presentation draws clear parallels between the need for precise classification and how we can minimize data waste and risk through effective data inventory management — both structured and unstructured data. During this presentation, you will learn:

• How to define a clear data classification scheme.
• Aligning classifications to your information security standards.
• Tagging and metadata management.
• Associating subject areas of data back to the business.
• Defining the system of record for each data group.
• Aligning structured and unstructured data classification.

Speaker: Steven Zagoudis

Steve Zagoudis is a data quality specialist and a leading authority on Lean Governance, Data Governance, Information Governance, and Data Risk Management strategies. He is the founder and CEO of MetaGovernance, an Enterprise Information Management (EIM) consulting firm. A veteran of advising multi-national corporations and government-sponsored enterprises (GSEs), Steve is passionate about helping organizations solve their critical data challenges.

Steve’s extensive background in Business Operations, IT, and Information Governance includes directing projects at Standard Oil, BP Worldwide, Sequent, IBM, Goldman-Sachs, and the Federal Home Loan Banks.

Steve is a strong advocate of governance controls in the world of structured and unstructured big data. Today’s regulatory environment is especially harsh for organizations that rely heavily on spreadsheets, end-user computing, and manual data reconciliations for financial disclosure.  For over 25 years he has helped clients across multiple industries improve their data accuracy and integrity while reducing operational, compliance, and reputation risk.