Breaking Down Barriers

Abstract:The nature of big data presents positive and negative impacts to our society, and quality professionals must learn how to survive and succeed in the big data world. They must change the way they think about sample size, exactitude, and causality. Using all data instead of small samples makes it possible to find connections and to explore details and subgroups. The second mindset change is to relax exactitude for probability. Entering the world of big data, you needn’t worry about individual data points biasing the overall analysis because you can rely on a large amount of data to make predictions. The third mindset change is to loosen up causality for correlation. In the big data age, powerful computing power can quickly identify the optimal proxies. Quality professionals must learn the skills associated with big data, such as statistics, rudimentary predictive modeling and basic computer programing, to leverage it in the decision-making process. They must learn how to work cohesively with …

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There are a lot of risks with Big Data, many of which were pointed out by Dr. Liu in this article. When there are tons of data, the tendancy is to just trust that past performance is a predictor of coming (potential) events. Yet, we do not live necessarily in a state of statistical control, and cannot always predict upcoming special causes that could change future outcomes (as in the stated example of a divorce based on a probability calculation of what COULD occur). Caution and "outside the box" thinking (a "practical" view) is even more needed now, which is pointed out with the changes needed in quality professionals.

The other caution is that as big data becomes increasingly more in use, the tools that are used need to adapt. Current data storage and computing systems may not handle the volume and complexity of data, and companies will tend to overstretch the limits of their systems, rather than invest in computing infrastructure. Todays new servers and storage solutions must be considered, and invested in wisely. And with that also comes new data protection solutions. CIO's must be an integral part of short and long-term capital planning.

Are all of you ready for this???
--Steve Ruegg, 01-28-2014

I think that even before statistical analysis and predictive modeling changes, we have to enable our staff to adjust to the data mining requirements of big data. As we get more data, we need to know how to access it properly in order to utilize it.
Second challenge is that with more data it is easy to think that we know what is going on without going to the source. With more possibility to analyze data, we have to make a more conscious effort to go to the gemba, lest we lose touch with the reality of the source of the data.
--Lloyd Gholson, 01-28-2014

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