In today’s world, as both data and fraud grow fast and furiously, reactive insight doesn’t work. Proactive insights are the new imperative. With billions of credit card transactions daily, American Express pushed traditional BI and insights to its limit. And when traditional cubes took more than four days to build (each only holding a quarter of the data), it was time for a change. Taking a modern approach to BI on Hadoop, American Express now shares immediate access with 2,000+ BI users across billions of rows of transaction data as it lands in Hadoop.
If you need to scale BI beyond what your traditional cubes and extracts allow you to, then BI on Hadoop is the right direction. Where do you start? What roles do you hire for? How do you architect it? How do you get buy-in from IT, analytics, and business users alike?
Bryan Harrison explores the BI and big data management challenges that IT and BI teams face today, providing prescriptive steps on how to architect and implement BI on Hadoop. Along the way, Bryan highlights American Express’s BI-on-Hadoop journey and architecture as an example of scale-out BI that meets the demands of massive billion-trillion-row data growth and access for 2,000+ decision makers that shows no signs of slowing anytime soon.
Bryan Harrison is vice president of credit and operational risk business intelligence at American Express. With more than 15 years’ business and IT experience in risk, analytics, and business intelligence capabilities leading global, complex projects spanning both business and IT organizations, Bryan has helped organizations manage strategic change with a combination of process improvement and innovation. Having held roles in both IT and analytics, Bryan understands the business and the technical side of BI and big data, enabling him to bridge the gap between people, processes, and technology.
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