The combination of increased regulations impacting data management, growing demand for accessibility to data assets for analytical purposes, and expansion of information management platforms beyond the traditional corporate boundaries means that ensuring data quality and usability is becoming more and more complex. Data governance programs are intended to establish oversight and control over enterprise information management processes and procedures. In a data governance program, defined data policies are intended to establish data quality assurance.
One of the biggest challenges, though, is transforming corporate data policies into processes and procedures for ensuring policy compliance. In this Geek Sync, we will look at the relationships between business policies and regulations, data policies, and five best practices to take advantage of tools and technologies to operationalize data governance. Attendees will learn about requirements analysis, data quality, business glossaries, data standards, data lineage, collaborative metadata, and data catalogs to support data governance.
About David: David Loshin is the president of Knowledge Integrity, Inc. and is a globally recognized thought leader and expert consultant in the areas of analytics, big data, data governance, data quality, master data management, and business intelligence. Along with consulting on numerous data management projects over the past 20 years, David is also a prolific author regarding data management best practices, including “Big Data Analytics: From Strategic Planning to Enterprise Integration with Tools, Techniques, NoSQL, and Graph,” the second edition of “Business Intelligence – The Savvy Manager’s Guide,” as well as other books and articles on data quality, master data management, big data, and data governance. David is a frequent invited speaker at conferences, web seminars, and sponsored web sites and TechTarget channels, and is the Program Director of the Master of Information Management program at the College of Information Studies at the University of Maryland.
Topics: Data Modeling, Data Governance, Metadata, Enterprise Architecture
Products: ER/Studio Business Architect