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Once social media and web companies discovered Hadoop as the good enough solution for any data analytics problem that did not fit into mysql, Hadoop was on a rapid rise on the financial industry. The reasons the financial industry is adopting Hadoop very fast are very different than in other industries. Banks typically are not engineering driven organizations and terms like agile development, shared root key or cron tab scheduling are no go’s in a bank but standard around Hadoop.
This entertaining talk for bankers and other financial services managers with technical experience or engineers discusses four business intelligence platform deployments on Hadoop:
1. Long-term storage and analytics of transactions and the huge cost saves Hadoop can provide;
2. Identifying cross and up sell opportunities by analyzing web log files in combination with customer profiles;
3. Value-at-risk analytics; and
4. Understanding the SLA issues and identifying problems in a thousands-of-nodes, big services oriented architecture.
This session discusses the different use cases and the challenges to overcome in building and using BI on Hadoop.
28th February to 1st March 2012