Webinar Data Catalog

Don't Get Fogged In!

Recorded Webcast: Using a Data Catalog to Lift Your Data Out of the Fog

Featured speakers

Andrew Ahn
Waterline Data

Michael Ferguson
Intelligent Business

Produced by MakeBigDataWork.org

In this educational webcast, join Mike Ferguson as he interviews Andrew Ahn of Waterline Data about best practices for using a data catalog.

Most big data is obscured. And just like finding something in a fog, you can only see it when you are near it or when it is so fresh that you remember exactly where it is. Whether your organization needs to perform big data analytics, comply with new data oriented regulations, or become more cost efficient by reducing the amount of redundant data in your organization, you need to know what data you have and where it is located.

The problem: proximity and freshness works for a very small amount of data. Meanwhile, the variety, volume, and velocity of data coming in continues to grow, and organizations become overwhelmed trying to make sense of it all.

Most organizations are relying on the “street light” method to find data, searching for it only where there’s already a streetlight shining—not necessarily where the data is located, so they don’t even know what data is available. This is where tribal knowledge traditionally comes in, but results are spotty. People forget. People leave. And people make mistakes. It’s critical to be able to quickly discover, understand and utilize your data to maintain a competitive advantage.

Watch this highly interactive session as we discuss:

  • How companies can lift the data fog and keep it lifted so business users can more readily find critical data and convert it into actionable business intelligence on an ongoing basis
  • Making automated tagging of data a part of the regular project workflow to kickstart the initial identification of data
  • Ways to curate automated results through Subject Matter Expert review
  • Maintaining the human element in the equation by retaining data stewards or analysts that can officially accept or reject a tag at any time
  • Establishing trust when it comes to the classification of your data to support tighter control over accessing and provisioning