Insight without action is worthless. Evan Stubbs, author of The Value of Business Analytics, explains that all of the data and insight you have is worthless to your company unless it is acted upon.
A better term for the “data scientist” may be “data artist,” says SAS’ Rachel Alt-Simmons. She explains how this role needs to embed a solution efficiently within a business process. And one way to do this is through the Lean methodology.
A reliable deployment system for analytic models is vital to successfully operationalizing analytics. Learn more in this article, part of a series on operationalizing analytics.
If you’re looking to operationalize analytics, you can’t do it without a repeatable, industrial-scale development process. Discover what that looks like in this article, part of a series on operationalizing analytics.
The first step to operationalizing analytics is understanding and solving the right problem. Find out how in this article, part of a series on operationalizing analytics based on a recent white paper by James Taylor, Decision Management Solutions.
Operationalizing analytics involves making analytics pervasive, predictive and actionable, says James Taylor, CEO, Decision Management Solutions. Hear more in this video.
Why do some still cling to intuition over the cold, hard facts? Accenture SAS Analytics Group research uncovers some reasons in this article.
The cost of raw materials has been volatile in recent years, so understanding costs is critical for profitability. In this article, Dow Chemical executives talk about how they use analytics to hedge against price swings and more effectively manage their businesses.
Many data mining business mistakes are obvious, like failing to define an objective or the very common, “we’re waiting on perfect data,” according to Jeff Deal, Vice President of Operations, Elder Research. Hear about more mistakes in this video interview.
Big data is most understood through pictures, says SAS’ Jennifer Marchi. She explains the latest in data visualization for organizations to see what is most important immediately.
“Predictive analytics is hot, the cloud is hot, so the intersection of the two is hot,” says James Taylor, CEO of Decision Management Solutions, as he discusses the scenarios of using predictive analytics in the cloud in this video interview.
Who is the “mountain climber” in your organization?
You’re only as good as what you can do
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