This post is part of a series on how the 9 Laws of Data Mining from Tom Khabaza can be applied to analytics. You can find previous posts here. Law #9: “Law of Change”: All patterns are subject to change All patterns change — not only because the data changes, but because our understanding of […]
This post is part of a series on how the 9 Laws of Data Mining from Tom Khabaza can be applied to analytics. You can find previous posts here. Law #8: “Value Law” – The value of data mining results [and analytics] is not determined by the accuracy or stability of predictive models In analytics,
Mega-retailer Target recently announced that it would be closing the doors of eleven locations by February 1, 2015. The company’s press release stated, “The decision to close a Target store is only made after careful consideration of the long-term financial performance of a particular location.”[i] Target’s team of site selection experts have certainly been doing
Did Target Miss the Mark? Recent Closings Explained With Analytics Read More »
This post is part of a series on how the 9 Laws of Data Mining from Tom Khabaza can be applied to analytics. You can find previous posts here. Law #6: “Insight Law” – Data mining [analytics] amplifies perception in the business domain Data mining tools are “perception amplifiers,” increasing our understanding of the business
Do Your Analytics Create Information Or Insight? Read More »
Many retailers today are faced with the daunting task of international store expansion, but for many looking to grow, the notion of expansion outside of the U.S. is a complex challenge. How are they to know, with confidence, which country they should expand into next? To appropriately develop and expand across a global platform of new/existing stores
Where Should We Grow Next? Using Data to Drive Decisions Read More »
Law #5: “Watkins’ Law” – There are always patterns [i] First, let’s talk about “The Good.” David Byrne, writing in the introduction to Gareth Cook’s book, The Best American Infographics, 2013, describes the power of the infographic as: “…an inbuilt ability to manipulate visual metaphors in ways we cannot do with the things and concepts they stand
Pattern Seekers: The Good, The Bad, and The Ugly Read More »
This post is part of a series on how the 9 Laws of Data Mining from Tom Khabaza can be applied to analytics. You can find previous posts here. The statement that “a piano makes music” is a clear misunderstanding. We all know that the pianist or any other musician is the source of the music and that
This post is part of a series on how the 9 Laws of Data Mining from Tom Khabaza can be applied to analytics. You can find previous posts on the 4C Blog. I grew up in the Amazon. (How and why is a topic for another forum.) Today, I am an analyst. Although there are few similarities between
Sculpting Your Clay: Analytics Lessons from the Amazon Read More »
This post is part of a series on the 9 Laws of Data Mining from Tom Khabaza applied to analytics. You can find previous posts here. Law #2: “Business Knowledge Law” – Business knowledge is central to every step of the data mining [market analytics] process Some might think that the best way to become
Tom Khabaza, an early innovator in the field of data mining in the 1990’s, developed the “9 Laws of Data Mining” in his lectures in 2010. Since then an entire community of data miners has benefited from these sound principles, but they have not been widely used by GIS professionals. These principles are a suitable
So, What? Setting Goals and Finding Answers in Location Analytics Read More »
