Are you sure you trust the data you just used for that $10 million decision? To trust data authenticity, we must first understand its lineage. However, the term "Data Lineage" itself is ambiguous since it is used in different contexts. "Business Lineage” links metadata constructs to specific terms in a business glossary. This approach is used by numerous Data Governance solutions. This approach alone comes up short, since it doesn't trace the real flow of information through an organization. "Technical Lineage" traces data's journey through different systems and data stores, providing an audit trail of the changes along the way. True "Data Lineage" combines both aspects, providing context to fully understand the data life cycle. Every step-in data's journey is a potential source for introduction of error that could compromise Data Quality, and hence, business decisions.
In this session, David Loshin offers a comprehensive discussion of data lineage and associated Data Quality remediation approaches that are essential to build a foundation for Data Governance.
David Loshin, president of Knowledge Integrity, Inc, (www.knowledge-integrity.com), is a recognized thought leader, TDWI instructor, and expert consultant in the areas of data management and business intelligence. David is a prolific author regarding business intelligence best practices, as the author of numerous books and papers on data management, including “Big Data Analytics: From Strategic Planning to Enterprise Integration with Tools, Techniques, NoSQL, and Graph” and “The Practitioner’s Guide to Data Quality Improvement,” with additional content provided at www.dataqualitybook.com. David is a frequent invited speaker at conferences, web seminars, and sponsored web sites and channels including TDWI, TechTarget and The Bloor Group. His best-selling book, “Master Data Management,” has been endorsed by many data management industry leaders. David is also Program Director for the Master of Information Management degree at the University of Maryland College of Information Studies.
Topics: Data Governance, Data Modeling, Enterprise Architecture Products: ER/Studio Enterprise Team Edition, ER/Studio Team Server Core