Basic Business Intelligence Reporting
January 23rd, 2012
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Take a CSV file and perform basic BI and reporting using a free tool.
Categories: data mining intelligence business, cube, data, data mining, intelligence, reports, software, tutorial, Warehouse
Archive
Archive for the ‘data mining intelligence’ Category
GBI Mining Intelligence – Dragline and Truck / Loader training
January 15th, 2012
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Through the thousands of years of data, GBI knows what it takes to be best practice, combined with our field trainers experience and opportunities recognised through interactions, we know what Dragline, Loader and Truck operators should be trained on!
How can you train effectively if you don’t know what best practice is?? We Do!
www.gbimining.com
gbi@gbimining.com
Duration : 0:3:1
Categories: data mining intelligence asset optimisation, Best, boom, Bucyrus, capacity, Caterpillar, coal, digging, dragline, gbi, gbimining, hitachi, iron, Komatsu, Libherr, marion, operator, ore, p&h, practicemineminingdipperbucket, productive, productivity, rigging, Safety, shovel, supervisor, swing, Terrex, train, training, truck
Chris Hote of Digimind – The Intelligence Collaborative Washington, DC 10/22/09
January 6th, 2012
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Chris Hote of Digimind explains his company’s web tracking and visualization software.
Duration : 0:1:38
BI Tutorial 12a Introducing Data Mining
December 29th, 2011
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qsftdbmgthttp://gdata.youtube.com/feeds/api/users/qsftdbmgtTechBI, Tutorial, 12a, Introducing, Data, MiningBI Tutorial 12a Introducing Data Mining
Duration : 0:14:55
Artificial Intelligence Lecture No. 17
December 21st, 2011
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Video of the Lecture No. 17 in Artificial Intelligence at Ravensburg-Weingarten University from December 5th 2011. The Topics are:
Clustering:
- k-Means and the EM Algorithm
- Hierarchical Clustering
- Distance between Clusters
- Farthest Neighbour Algorithm
Data Mining in Practice
- The Data Mining Tool KNIME
Duration : 1:32:28
Categories: data mining intelligence AI, artificial intelligence, Clustering, computer, data mining, Distance between Clusters, EM Algorithm, Ertel, Farthest Neighbour Algorithm, FH Ravensburg, FH Ravensburg-Weingarten, FH Weingarten, Hierachical Clustering, HS Ravensburg-Weingarten, k-Means, k-Means and the EM Algorithm, KI, KNIME, Künstliche Intelligent, Lecture, Prof. Ertel, Ravensburg, Vorlesung, Weingarten, Wolfgang Ertel