Companies today face increasing pressure to capitalize on Big Data, which is increasingly a cost of doing business rather than a competitive advantage. They are making substantial investments to collect and analyze the ever-growing volume of available data.

This pressure has led many companies to make decisions without planning ahead for data management and governance, thereby hamstringing their ability to mine the data they are collecting. The base principals of data management and governance not only still apply but actually become even more important in Big Data implementations.

This presentation will discuss the critical data governance and metadata best practices that drive Big Data success based on practical project examples. These include but are not limited to:

• The Ability to capture custom business metadata
• Automatic cataloging of Hadoop technical metadata
• Search capability to enable data discovery in the data hub / lake
• Full data Lineage at both the file and column level