Category Archives: Data Mining and Predictive Analytics

Planning a 1-Day Symposium in Boise on the Utilization of Graph-Centric Data Technologies in Business Intelligence

Introduction I’m currently working with the organizers of the Boise BI User Group and a few heavy hitters from various Boise-based technology communities on a 1-day symposium introducing graph-based technologies to those in the Boise Business Intelligence community. (To clarify, by “graphs”, I’m referring … Continue reading

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What I Would Have Said at TEDx Boise 2015 Had I Been Selected

I applied to speak at the inaugural TEDx Boise 2015 event, but I was not selected. However, I would still like to share what I had intended to say had I been chosen. The Synopsis is what I submitted to the Selection Committee … Continue reading

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Protected: Embracing Complexity – Pt 2 of 6 – Data Prep and Pattern Recognition

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Levels of Pain – Refining the “Bad” side of the KPI Status

Everything we do towards achieving goals involves costs – sacrifice, investment (a positive way to look at it). We purposefully put things we already have (time, money, our career) to be consumed or at risk in the hope of achieving a … Continue reading

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The Magic of the Whole is Greater than the Sum of Its Parts

Prelude If businesses were people, they would lumber about in a vaguely purposeful manner like zombies. That’s due to the top-down, military-style hierarchies of modern corporations that result in integration of information only at the top and only to a limited extent below. … Continue reading

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Cluster Drift

A deficiency I notice in practically every implementation of clustering (segmentation) is the snapshot mentality. For example, a vendor of a product would segment their customers in an attempt to isolate the ones who would be most likely to buy their … Continue reading

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Find and Measure Relationships in Your OLAP Cubes

Huge strides in the value proposition of BI will come by jumping the chasm from simply reporting on data provided by the integrated view of our enterprise to discovering novel and perhaps counter-intuitive relationships hidden in that data. With the discovery of such relationships, we … Continue reading

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