 | | Doug Henschen | | | | | It was fitting that the moderator of the kick-off keynote panel at last week's Seventh Annual MIT Sloan Sports Analytics Conference in Boston was Michael Lewis, author of the recent bestseller The Big Short, about the financial crisis, and of the seminal 2003 book Moneyball, which captured the pioneering use of analytics in baseball by the Oakland Athletics.
Lewis was joined by Mark Cuban, owner of the NBA's Dallas Mavericks; Paraag Marathe, COO of the San Francisco 49ers; Daryl Morey, head of basketball operations at the Houston Rockets; and Nate Silver, the famously accurate predictor of the 2012 presidential election, who got his start as developer of the PECOTA system for forecasting the performance and development of Major League Baseball players.
What advice did these analytics pioneers have to share on numbers-driven decision-making? Here are four themes that apply no matter what industry you're in. READ MORE | |  | | JOIN THE CONVERSATION Posted By By S. Auge: "Context is needed. For example, data on products no longer made or serviced probably aren't wanted by operations--especially manufacturing. However, sales and marketing may want to know about the previous purchases and the customer's last contact time.
"Of course, if a customer went bankrupt, marketing and sales will likely think that information is stale. However, manufacturing/operations may find any comments and/or service requests useful to determine if something is going wrong with a product over time." In reply to: Are You A Data Hoarder? View Entire Response | Post Your Own Reply  | | COMMENTARY REPORTS & WHITEPAPERS FEATURED REPORTS
Best Practices: A Guide To Practical Database Monitoring
With so much important data at stake, many enterprises have come to realize that database activity monitoring (DAM) is a critical element of both data and database security. DAM products are a mainstream data security technology, used by more than half of Fortune 500 companies. They help secure information and address compliance requirements in a manner no other product can. But sometimes the practical realities of DAM tools and practices are different than they look in a vendor demonstration. In this report, we take a look at how DAM operates in a live enterprise; what works, what doesn't, and how some of the benefits sold to customers are theoretically possible but often impractical.
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| | |  | | | FEATURED WHITEPAPERS Big Data In Trading And Risk Management This industry briefing, sponsored by SAP, provides insight and analysis on how financial markets firms see big data approaches and technologies being leveraged for trading and risk applications. Respondents demonstrated a good understanding of how big data approaches might be leveraged across a number of key trading and risk applications, with substantial commonality of thought in some cases.
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| Big Data. Big Decisions. From Enterprise Software And SAS
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