Comments on: Where does data mining succeed, and why? http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/ Technology ... politics ... marketing ... strategy ... life Wed, 08 Sep 2010 09:52:33 -0400 http://wordpress.org/?v=2.8.4 hourly 1 By: The Monash Report»Blog Archive » Three ways to market analytics-related technology http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-6695 The Monash Report»Blog Archive » Three ways to market analytics-related technology Mon, 19 Mar 2007 08:57:58 +0000 http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-6695 [...] Data mining and predictive analytics are mainly information access plays. Yes, the information being accessed is calculated rather than raw. Yes, I believe that the heart of the data mining market is continuous process improvement. Even so, what users buy from the vendors is usually little more than information toolkits. [...] [...] Data mining and predictive analytics are mainly information access plays. Yes, the information being accessed is calculated rather than raw. Yes, I believe that the heart of the data mining market is continuous process improvement. Even so, what users buy from the vendors is usually little more than information toolkits. [...]

]]> By: The Monash Report»Blog Archive » The problem with dashboards, and business intelligence segmented http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-2501 The Monash Report»Blog Archive » The problem with dashboards, and business intelligence segmented Fri, 06 Oct 2006 01:02:57 +0000 http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-2501 [...] Nor does this change when the warnings are the product of text or data mining. For example, despite a very interesting approach to generating alerts, at this point in its development Verix delivers them in uninspired ways. [...] [...] Nor does this change when the warnings are the product of text or data mining. For example, despite a very interesting approach to generating alerts, at this point in its development Verix delivers them in uninspired ways. [...]

]]> By: DBMS2 — DataBase Management System Services»Blog Archive » Data warehouse and mart uses – a tentative taxonomy http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-1964 DBMS2 — DataBase Management System Services»Blog Archive » Data warehouse and mart uses – a tentative taxonomy Sun, 24 Sep 2006 05:29:41 +0000 http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-1964 [...] Finally, there is hardcore data crunching. Data mining fits that bill, but so does heavy SQL-only data exploration (aka “The Query That Ate Pittsburgh”). This is where a small number of expert users extract value from massive data stores. Scheduled reporting can also fit into this category at aggressive enterprises. Here is where the high-end data warehouse vendors – e.g., Teradata, IBM (mainframe DB2), and the data warehouse appliance startups – really shine. At smaller enterprises, other kinds of data stores also suffice. I have a careful list (two versions of the same list, actually) of data mining app categories over on the Monash Report. It’s a good start on a list of apps for this whole category. [...] [...] Finally, there is hardcore data crunching. Data mining fits that bill, but so does heavy SQL-only data exploration (aka “The Query That Ate Pittsburgh”). This is where a small number of expert users extract value from massive data stores. Scheduled reporting can also fit into this category at aggressive enterprises. Here is where the high-end data warehouse vendors – e.g., Teradata, IBM (mainframe DB2), and the data warehouse appliance startups – really shine. At smaller enterprises, other kinds of data stores also suffice. I have a careful list (two versions of the same list, actually) of data mining app categories over on the Monash Report. It’s a good start on a list of apps for this whole category. [...]

]]> By: Curt Monash http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-1910 Curt Monash Tue, 12 Sep 2006 04:05:13 +0000 http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-1910 James Taylor attempted to post this comment but for some reason failed. So I'm doing it for him. I'm doing this from vacation on Grand Cayman, after a hard day of snorkeling (revelation of the day -- "beautiful squid" is NOT an oxymoron), so please forgive my lack of effort to fix word wrap and any other formatting issues. (But at least I fixed the typo in one of the URLs ...) CAM ---------------------------------------------------------- Curt Think you are completely correct on this one - the ongoing management and improvement of decisions using data mining is where the money is. One of the challenges this raises is how to "operationalize" the insight that comes from data mining. One way is to mine the data for business rules and operationalize those and another is to mine the data so as to produce executable predictive analytic models. I have written about a one-time immediate improvement ( http://www.edmblog.com/weblog/2005/10/customer_segmen.html ) but more have the kind of ongoing success you discuss. There's a lot of confusion around data mining, analytics, predictive analytics and so on so it comes up a lot on my blog at http://www.edmblog.com/weblog/data_mining/index.html. One last thing - this poll at KD Nuggets was fun http://www.edmblog.com/weblog/2005/08/kdnuggets_succe.html. James Taylor attempted to post this comment but for some reason failed. So I’m doing it for him.

I’m doing this from vacation on Grand Cayman, after a hard day of snorkeling (revelation of the day — “beautiful squid” is NOT an oxymoron), so please forgive my lack of effort to fix word wrap and any other formatting issues. (But at least I fixed the typo in one of the URLs …) CAM
———————————————————-

Curt

Think you are completely correct on this one – the ongoing management
and improvement of decisions using data mining is where the money is.
One of the challenges this raises is how to “operationalize” the insight
that comes from data mining. One way is to mine the data for business
rules and operationalize those and another is to mine the data so as to
produce executable predictive analytic models.

I have written about a one-time immediate improvement
( http://www.edmblog.com/weblog/2005/10/customer_segmen.html ) but more
have the kind of ongoing success you discuss. There’s a lot of confusion
around data mining, analytics, predictive analytics and so on so it
comes up a lot on my blog at
http://www.edmblog.com/weblog/data_mining/index.html.

One last thing – this poll at KD Nuggets was fun
http://www.edmblog.com/weblog/2005/08/kdnuggets_succe.html.

]]> By: The Monash Report»Blog Archive » My actual column on data mining http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-1908 The Monash Report»Blog Archive » My actual column on data mining Tue, 12 Sep 2006 03:59:14 +0000 http://www.monashreport.com/2006/09/08/where-does-data-mining-succeed-and-why/#comment-1908 [...] In a couple of recent posts about data mining, I referenced a Computerworld column due to run September 11. Wonder of wonders, they got it posted on the very first day. Here’s a link. • • • [...] [...] In a couple of recent posts about data mining, I referenced a Computerworld column due to run September 11. Wonder of wonders, they got it posted on the very first day. Here’s a link. • • • [...]

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