"Where are you standing today with the project?
I think that the 4 categories may interlink. Fraudulent Patterns, Incentives, Resource leveling, and Projections – all benefit from being able to identify the phenomena and key factors of…"
"Strange my answer disappeared; here again:
Data mining is everything that Statistics is not, conceptually and practically.
1. Data mining role is to define hypotheses, to be run later by Statistics.
2. DM is algorithms while Statistics is a set of…"
"I'd try first to do data mining on the audience database + any previous survey in the past year or two.
The analysis should bring up patterns, some of which may indicate HIDDEN POTENTIAL MARKET.
Also, each pattern is characterized by a number…"
Complex-and-unsupervised analytics specialist; the developer of GT data mining analytics, Founder &CEO of Procedureware.
Currently engaged in SaaS type projects, and extending GT for extensive data analytics.
GT development started in 2002, Singapore.
Education: Industrial & Management Engineer, from the Thechnion in Haifa Israel, MS in Economic Systems from NY Polytechnic.
The fall of the Lehman Brothers and Merrill Lynch - two companies rich in BI tools, calls for questioning the validity of those tools. Anybody knows which were the BI solutions that served in them?
To my mind, giving early warning about critical situations, is the ultimate test of a BI system. For a long time I say that statistics based analytics cannot perform this crucial test task. What we witness now may be the sad realization of that.
And a personal note: my solution, GT data mining, is not based on statistics, which enables it to interpret the data independently of users' assumptions.