“Big data” relies on consumption of massive volumes and varieties of data marked by inconsistencies across different sources, questionable lineage, and uncertain data currency. Integrating unstructured and structured data sets implies that small variances in semantics, concept tagging, and terminology will have adverse impacts on consumers of business analytics. Some aspects of conventional data quality practices are insufficient to meet the emerging needs of the analytical community, while others have never been more important. In this talk we explore the aspects of data quality that will deliver the greatest value in today's challenging big data environments.
Attendees will learn about some key points for helping ensure the quality of big data, including:
TDWI and IBM Content
Individual, Student, & Team memberships available.