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John Sall to talk big data, big statistics, big graphics at Discovery Summit 2012

Analytics has come a long way since 1976, the year John Sall joined Jim Goodnight and two others to establish SAS. And many JMP users have come a long way since the late 1980s, when Sall created JMP software to dynamically link statistical analysis with graphics.

JMP continues to play an important role in modeling processes across industries as a desktop data visualization tool. It also provides a visual interface to SAS in an expanding line of solutions.

These days, organizations have lots of data and the ability to process it amazingly fast, but they still need ways to look at it without being overwhelmed.

Sall will deliver a keynote speech at Discovery Summit 2012 on Sept. 11 at SAS world headquarters. He'll talk about big data, big statistics and big graphics.

“We don't want to look at 10,000 graphs,” says Sall. “We want a minimal number of graphs, and sometimes interactive graphs, to see the bright spots in the 10,000 graphs.

“We want the computer and the software to do the lion’s share of the work of finding what is most interesting and bringing it to our attention. We want our results sorted and summarized, but still with access to the detail that we need to understand it. Also, when we look at the most significant of thousands of statistical tests, we want to know if we are seeing random coincidence selected out of thousands or if we are seeing real effects.”

Sall says that when massive sample sizes give tiny effects statistical significance, we need to ask for an assessment of their practical significance to determine when the effect warrants further examination. Genomics researchers have pioneered the use of methods that address this problem, such as corrections that adjust for the performance of multiple similar tests. As data sets continue to increase in size across all disciplines, so does the need for tools to analyze at scale – and spot patterns at scale.

“We look forward to next year, the International Year of Statistics, where we can show the world how to harness statistics to address big challenges,” says Sall.

Big data needs big statistics and big graphics.

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