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Description:

While the rest of the world is coming to grips with volume, velocity, and variety, you stand there with your hands in the air yelling, "Wait! How can we be sure this is good data?" And you're right to raise this important question. Nobody is thinking about the "veracity" of the information coming in.

Experts estimate that inaccurate data costs U.S. businesses $700 billion each year. The average annual financial impact on individual companies is a whopping $13.3 million. These figures don't even account for hidden costs such as reputation damage, loss of confidence or inability to plan.

As your organization shapes up to embrace big data to build new insights, who is thinking about the implications of data quality? Who is thinking about how to assess and ensure quality at this massive scale? If you're a data analyst or data scientist, that's where you come in.

In this webcast, you will learn how to:

• Blend traditional questions with a new way of thinking to ensure data quality.
• Prepare yourself to add veracity to your big data by connecting to trusted data quality tools directly from Hadoop.
• Help your organization embrace insights on big data that can be trusted.
• Measure the quality of the data available to you.

About Scott Arnett, Dir. Product Management, Customer Information Management – Pitney Bowes

Scott Arnett has been the Director of Product Management for Spectrum Customer Information Management with Pitney Bowes since 2014. Arnett has worked in the data integration and business intelligence world since 1996, when he joined Sagent Technology, an early pioneer in the data warehousing and data integration market. Arnett has held a number of positions as both Product Manager and Technical Support Manager over his career. He graduated from University of The Pacific and currently lives in San Jose, CA.