Data Quality: The 800 Pound Gorilla

Much of the Business Intelligence reporting, Analytics, and Data Visualizations contain data errors that are hidden, because the sources are fraught with anomalies and inconsistencies. In most organizations, data quality issues lead to erroneous decisions and lost opportunities. Is your organization allowing the 800 pound Gorilla to be ignored and cause chaos?

Join us as we share insights on how we have been fighting this beast by overcoming obstacles and demonstrating results:

Common Data Quality issues and their impact on your organization, understanding issues lurking in the shadows
Overcoming the lack of understanding and the obstacles between the business teams and technology groups
Real life case studies for performing Data Quality Assessments and using the assessment results
Being Proactive versus Reactive and the impact of doing nothing
Leveraging a Data Architecture to make the process repeatable

Deborah Torhanova is a Senior Data Analyst at JM Family Enterprises. Deborah has over 25 years experience in Information Technology and has held various roles in Database Development, Application Design and Development, Data Integration, and Data Warehousing. She is currently working on engagements with JM Family's Data Governance and Data Science teams.

Deborah's interests in data management include working with business teams to understand data assets through the use of tools and techniques that explore data quality, lineage, and metadata. Deborah has a Bachelor's Degree in Management Information Systems.

Ray Diaz is a Senior Data Analyst, Certified Business Intelligence Professional, Certified Data Management Professional, and Certified Scrum Master for the Enterprise Competency Center at JM Family Enterprises. Ray is a conference speaker with a mission to influence organizations on creating value persistently and delivering projects through the Business Intelligence, Analytics, and Data Management domains. Ray's projects include data integration with enterprise Cloud applications, Data Quality assessments, and Data analysis and preparation for Analytics and Dashboards.